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Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynamic execution sandboxes for every repository, which are expensive and computationally heavy. Using large language model (LLM) reasoning instead of executing the code is rising in popularity to bypass this overhead, yet it frequently leads to unsupported guesses and hallucinations. To improve execution-free reasoning, researchers at Meta introduce "semi-formal reasoning," a structured prompting technique. This method requires the AI agent to fill out a logical certificate by explicitly stating premises, tracing concrete execution paths, and deriving formal conclusions before providing an answer. The structured format forces the agent to systematically gather evidence and follow function calls before drawing conclusions. This increases the accuracy of LLMs in coding tasks and significantly reduces errors in fault localization and codebase question-answering. For developers using LLMs in code review tasks, semi-formal reasoning enables highly reliable, execution-free semantic code analysis while drastically reducing the infrastructure costs of AI coding systems. Agentic code reasoning Agentic code reasoning is an AI agent's ability to navigate files, trace dependencies, and iteratively gather context to perform deep semantic analysis on a codebase without running the code. In enterprise AI applications, this capability is essential for scaling automated bug detection, comprehensive code reviews, and patch verification across complex repositories where relevant context spans multiple files. The industry currently tackles execution-free code verification through two primary approaches. The first involves unstructured LLM evaluators that try to verify code either directly or by training specialized LLMs as reward models to approximate test outcomes. The major drawback is their

Imagine if your Teams or Slack messages automatically turned into secure context for your AI agents — PromptQL built it

For the modern enterprise, the digital workspace risks descending into "coordination theater," in which teams spend more time discussing work than executing it. While traditional tools like Slack or Teams excel at rapid communication, they have structurally failed to serve as a reliable foundation for AI agents, such that a Hacker News thread went viral in February 2026 calling upon OpenAI to build its own version of Slack to help empower AI agents, amassing 327 comments. That's because agents often lack the real-time context and secure data access required to be truly useful, often resulting in "hallucinations" or repetitive re-explaining of codebase conventions. PromptQL, a spin-off from the GraphQL unicorn Hasura, is addressing this by pivoting from an AI data tool into a comprehensive, AI-native workspace designed to turn casual, regular team interactions into a persistent, secure memory for agentic workflows — ensuring these conversations are not simply left by the wayside or that users and agents have to try and find them again later, but rather, distilled and stored as actionable, proprietary data in an organized format — an internal wiki — that the company can rely on going forward, forever, approved and edited manually as needed. Imagine two colleagues messaging about a bug that needs to be fixed — instead of manually assigning it to an engineer or agent, your messaging platform automatically tags it, assigns it and documents it all in the wiki with one click Now do this for every issue or topic of discussion that takes place in your enterprise, and you'll have an idea of what PromptQL is attempting. The idea is a simple but powerful one: turning the conversation that necessarily precedes work into an actual assignment that is automatically started by your own messaging system. “We don’t have conversations about work anymore," CEO Tanmai Gopal said in a recent video call interview with VentureBeat. "You actually have conversations that do the work.” Origina

Softr launches AI-native platform to help nontechnical teams build business apps without code

Softr, the Berlin-based no-code platform used by more than one million builders and 7,000 organizations including Netflix, Google, and Stripe, today launched what it calls an AI-native platform — a bet that the explosive growth of AI-powered app creation tools has produced a market full of impressive demos but very little production-ready business software. The company's new AI Co-Builder lets non-technical users describe in plain language the software they need, and the platform generates a fully integrated system — database, user interface, permissions, and business logic included — connected and ready for real-world deployment immediately. The move marks a fundamental evolution for a company that spent five years building a no-code business before layering AI on top of what it describes as a proven infrastructure of constrained, pre-built building blocks. "Most AI app-builders stop at the shiny demo stage," Softr Co-Founder and CEO Mariam Hakobyan told VentureBeat in an exclusive interview ahead of the launch. "A lot of the time, people generate calculators, landing pages, and websites — and there are a huge number of use cases for those. But there is no actual business application builder, which has completely different needs." The announcement arrives at a moment when the AI app-building market finds itself at an inflection point. A wave of so-called "vibe coding" platforms — tools like Lovable, Bolt, and Replit that generate application code from natural language prompts — have captured developer mindshare and venture capital over the past 18 months. But Hakobyan argues those tools fundamentally misserve the audience Softr is chasing: the estimated billions of non-technical business users inside companies who need custom operational software but lack the skills to maintain AI-generated code when it inevitably breaks. Why AI-generated app prototypes keep failing when real business data is involved The core tension Softr is trying to resolve is one that has plag

ScaleOps raises $130M to improve computing efficiency amid AI demand

ScaleOps just raised $130M to tackle GPU shortages and soaring AI cloud costs by automating infrastructure in real time.

When AI turns software development inside-out: 170% throughput at 80% headcount

Many people have tried AI tools and walked away unimpressed. I get it — many demos promise magic, but in practice, the results can feel underwhelming. That’s why I want to write this not as a futurist prediction, but from lived experience. Over the past six months, I turned my engineering organization AI-first. I’ve shared before about the system behind that transformation — how we built the workflows, the metrics, and the guardrails. Today, I want to zoom out from the mechanics and talk about what I’ve learned from that experience — about where our profession is heading when software development itself turns inside out. Before I do, a couple of numbers to illustrate the scale of change. Subjectively, it feels that we are moving twice as fast. Objectively, here’s how the throughput evolved. Our total engineering team headcount floated from 36 at the beginning of the year to 30. So you get ~170% throughput on ~80% headcount, which matches the subjective ~2x. Zooming in, I picked a couple of our senior engineers who started the year in a more traditional software engineering process and ended it in the AI-first way. [The dips correspond to vacations and off-sites]: Note that our PRs are tied to JIRA tickets, and the average scope of those tickets didn’t change much through the year, so it’s as good a proxy as the data can give us. Qualitatively, looking at the business value, I actually see even higher uplift. One reason is that, as we started last year, our quality assurance (QA) team couldn’t keep up with our engineers' velocity. As the company leader, I wasn’t happy with the quality of some of our early releases. As we progressed through the year, and tooled our AI workflows to include writing unit and end-to-end tests, our coverage improved, the number of bugs dropped, users became fans, and the business value of engineering work multiplied. From big design to rapid experimentation Before AI, we spent weeks perfecting user flows before writing code. It made sense

IndexCache, a new sparse attention optimizer, delivers 1.82x faster inference on long-context AI models

Processing 200,000 tokens through a large language model is expensive and slow: the longer the context, the faster the costs spiral. Researchers at Tsinghua University and Z.ai have built a technique called IndexCache that cuts up to 75% of the redundant computation in sparse attention models, delivering up to 1.82x faster time-to-first-token and 1.48x faster generation throughput at that context length. The technique applies to models using the DeepSeek Sparse Attention architecture, including the latest DeepSeek and GLM families. It can help enterprises provide faster user experiences for production-scale, long-context models, a capability already proven in preliminary tests on the 744-billion-parameter GLM-5 model. The DSA bottleneck Large language models rely on the self-attention mechanism, a process where the model computes the relationship between every token in its context and all the preceding ones to predict the next token. However, self-attention has a severe limitation. Its computational complexity scales quadratically with sequence length. For applications requiring extended context windows (e.g., large document processing, multi-step agentic workflows, or long chain-of-thought reasoning), this quadratic scaling leads to sluggish inference speeds and significant compute and memory costs. Sparse attention offers a principled solution to this scaling problem. Instead of calculating the relationship between every token and all preceding ones, sparse attention optimizes the process by having each query select and attend to only the most relevant subset of tokens. DeepSeek Sparse Attention (DSA) is a highly efficient implementation of this concept, first introduced in DeepSeek-V3.2. To determine which tokens matter most, DSA introduces a lightweight "lightning indexer module" at every layer of the model. This indexer scores all preceding tokens and selects a small batch for the main core attention mechanism to process. By doing this, DSA slashes the heavy co

Federal Cyber Experts Called Microsoft's Cloud "A Pile of Shit", yet Approved It

Fixing AI failure: Three changes enterprises should make now

Recent reports about AI project failure rates have raised uncomfortable questions for organizations investing heavily in AI. Much of the discussion has focused on technical factors like model accuracy and data quality, but after watching dozens of AI initiatives launch, I’ve noticed that the biggest opportunities for improvement are often cultural, not technical. Internal projects that struggle tend to share common issues. For example, engineering teams build models that product managers don’t know how to use. Data scientists build prototypes that operations teams struggle to maintain. And AI applications sit unused because the people they were built for weren't involved in deciding what “useful” really meant. In contrast, organizations that achieve meaningful value with AI have figured out how to create the right kind of collaboration across departments, and established shared accountability for outcomes. The technology matters, but the organizational readiness matters just as much. Here are three practices I’ve observed that address the cultural and organizational barriers that can impede AI success. Expand AI literacy beyond engineering When only engineers understand how an AI system works and what it’s capable of, collaboration breaks down. Product managers can't evaluate trade-offs they don't understand. Designers can't create interfaces for capabilities they can't articulate. Analysts can't validate outputs they can't interpret. The solution isn't making everyone a data scientist. It's helping each role understand how AI applies to their specific work. Product managers need to grasp what kinds of generated content, predictions or recommendations are realistic given available data. Designers need to understand what the AI can actually do so they can design features users will find useful. Analysts need to know which AI outputs require human validation versus which can be trusted. When teams share this working vocabulary, AI stops being something that happens in

Bump ruby_llm from 1.2.0 to 1.13.2

Bumps [ruby_llm](https://github.com/crmne/ruby_llm) from 1.2.0 to 1.13.2. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/crmne/ruby_llm/releases">ruby_llm's releases</a>.</em></p> <blockquote> <h2>1.13.2</h2> <h1>RubyLLM 1.13.2: Patch Fixes for Schema + Streaming 🐛🔧</h1> <p>A small patch release with three fixes.</p> <h2>🧩 Fix: Schema Names Are Always OpenAI-Compatible</h2> <p>Schema names now always produce a valid <code>response_format.json_schema.name</code> for OpenAI:</p> <ul> <li>namespaced names like <code>MyApp::Schema</code> are sanitized</li> <li>blank names now safely fall back to <code>response</code></li> </ul> <p>Fixes <a href="https://redirect.github.com/crmne/ruby_llm/issues/654">#654</a>.</p> <h2>🌊 Fix: Streaming Ignores Non-Hash SSE Payloads</h2> <p>Streaming handlers now skip non-Hash JSON payloads (like <code>true</code>) before calling provider chunk builders, preventing intermittent crashes in Anthropic streaming.</p> <p>Fixes <a href="https://redirect.github.com/crmne/ruby_llm/issues/656">#656</a>.</p> <h2>🗓️ Fix: models.dev <code>created_at</code> Date Handling</h2> <p>Improved handling for missing <code>models.dev</code> dates when populating <code>created_at</code> metadata.</p> <h2>Installation</h2> <pre lang="ruby"><code>gem &quot;ruby_llm&quot;, &quot;1.13.2&quot; </code></pre> <h2>Upgrading from 1.13.1</h2> <pre lang="bash"><code>bundle update ruby_llm </code></pre> <h2>Merged PRs</h2> <ul> <li>Fix missing models.dev date handling for created_at metadata by <a href="https://github.com/afurm"><code>@​afurm</code></a> in <a href="https://redirect.github.com/crmne/ruby_llm/pull/652">crmne/ruby_llm#652</a></li> <li>[BUG] Fix schema name sanitization for OpenAI API compatibility by <a href="https://github.com/alexey-hunter-io"><code>@​alexey-hunter-io</code></a> in <a href="https://redirect.github.com/crmne/ruby_llm/pull/655">crmne/ruby_llm#655</a></li> <li>Fix Anthropic streaming crash on non-hash SSE payloads by <a href="https://github.com/crmne"><code>@​crmne</code></a> in <a href="https://redirect.github.com/crmne/ruby_llm/pull/657">crmne/ruby_llm#657</a></li> </ul> <p><strong>Full Changelog</strong>: <a href="https://github.com/crmne/ruby_llm/compare/1.13.1...1.13.2">https://github.com/crmne/ruby_llm/compare/1.13.1...1.13.2</a></p> <h2>1.13.1</h2> <h1>RubyLLM 1.13.1: Quick Fixes 🐛🔧</h1> <p>A small patch release with three fixes.</p> <h2>🧩 Fix: Schema + Tool Calls No Longer Crash</h2> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/crmne/ruby_llm/commit/0950693544457b840cee7f7c89e69248f5f32de6"><code>0950693</code></a> Updated cassettes</li> <li><a href="https://github.com/crmne/ruby_llm/commit/b6e62a6df45e6445a91d41ff71440deec1ea8d88"><code>b6e62a6</code></a> Bump to 1.13.2</li> <li><a href="https://github.com/crmne/ruby_llm/commit/67c41488c3fba7af4eea5777c799c3e4789bb38e"><code>67c4148</code></a> Fix Anthropic streaming crash on non-hash SSE payloads (<a href="https://redirect.github.com/crmne/ruby_llm/issues/657">#657</a>)</li> <li><a href="https://github.com/crmne/ruby_llm/commit/afe7d046eb102c42137ee1aac338df861bca8637"><code>afe7d04</code></a> [BUG] Fix schema name sanitization for OpenAI API compatibility (<a href="https://redirect.github.com/crmne/ruby_llm/issues/655">#655</a>)</li> <li><a href="https://github.com/crmne/ruby_llm/commit/fe8994d56640d56112d1afa82d95014a2df967d6"><code>fe8994d</code></a> Updated models</li> <li><a href="https://github.com/crmne/ruby_llm/commit/48bf6f6c98a15ed53501bdabc36cc9fc740bec30"><code>48bf6f6</code></a> Updated models</li> <li><a href="https://github.com/crmne/ruby_llm/commit/d940984d0b3cf63f108a7e0df52db82238ff8549"><code>d940984</code></a> Fix missing models.dev date handling for created_at metadata (<a href="https://redirect.github.com/crmne/ruby_llm/issues/652">#652</a>)</li> <li><a href="https://github.com/crmne/ruby_llm/commit/97c0546d8e09cfd51943ae612d9598ab11e81885"><code>97c0546</code></a> Bump to 1.13.1</li> <li><a href="https://github.com/crmne/ruby_llm/commit/10949459d1243cc2a7c1ebef3a8ce9ac9691bb71"><code>1094945</code></a> Populate Gemini cached token usage</li> <li><a href="https://github.com/crmne/ruby_llm/commit/beec83752c7697465b0f6f9e50b8bdfbc25353d1"><code>beec837</code></a> Fix schema JSON parsing for intermediate tool-call responses (<a href="https://redirect.github.com/crmne/ruby_llm/issues/650">#650</a>)</li> <li>Additional commits viewable in <a href="https://github.com/crmne/ruby_llm/compare/1.2.0...1.13.2">compare view</a></li> </ul> </details> <br /> [](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compat

chore(deps): update updates-patch-minor

> ℹ️ **Note** > > This PR body was truncated due to platform limits. This PR contains the following updates: | Package | Update | Change | |---|---|---| | 1password/connect-sync | patch | `1.8.1` → `1.8.2` | | [alpine/openclaw](https://openclaw.ai) ([source](https://redirect.github.com/openclaw/openclaw)) | minor | `2026.2.22` → `2026.3.8` | | [cloudflare/cloudflared](https://redirect.github.com/cloudflare/cloudflared) | minor | `2026.2.0` → `2026.3.0` | | kerberos/agent | patch | `v3.6.12` → `v3.6.15` | | [searxng/searxng](https://searxng.org) ([source](https://redirect.github.com/searxng/searxng)) | patch | `2026.3.8-a563127a2` → `2026.3.9-d4954a064` | --- > [!WARNING] > Some dependencies could not be looked up. Check the [Dependency Dashboard](../issues/304) for more information. --- ### Release Notes <details> <summary>openclaw/openclaw (alpine/openclaw)</summary> ### [`v2026.3.8`](https://redirect.github.com/openclaw/openclaw/blob/HEAD/CHANGELOG.md#202638) [Compare Source](https://redirect.github.com/openclaw/openclaw/compare/v2026.3.7...v2026.3.8) ##### Changes - CLI/backup: add `openclaw backup create` and `openclaw backup verify` for local state archives, including `--only-config`, `--no-include-workspace`, manifest/payload validation, and backup guidance in destructive flows. ([#&#8203;40163](https://redirect.github.com/openclaw/openclaw/issues/40163)) thanks [@&#8203;shichangs](https://redirect.github.com/shichangs). - macOS/onboarding: add a remote gateway token field for remote mode, preserve existing non-plaintext `gateway.remote.token` config values until explicitly replaced, and warn when the loaded token shape cannot be used directly from the macOS app. ([#&#8203;40187](https://redirect.github.com/openclaw/openclaw/issues/40187), supersedes [#&#8203;34614](https://redirect.github.com/openclaw/openclaw/issues/34614)) Thanks [@&#8203;cgdusek](https://redirect.github.com/cgdusek). - Talk mode: add top-level `talk.silenceTimeoutMs` config so Talk waits a configurable amount of silence before auto-sending the current transcript, while keeping each platform's existing default pause window when unset. ([#&#8203;39607](https://redirect.github.com/openclaw/openclaw/issues/39607)) Thanks [@&#8203;danodoesdesign](https://redirect.github.com/danodoesdesign). Fixes [#&#8203;17147](https://redirect.github.com/openclaw/openclaw/issues/17147). - TUI: infer the active agent from the current workspace when launched inside a configured agent workspace, while preserving explicit `agent:` session targets. ([#&#8203;39591](https://redirect.github.com/openclaw/openclaw/issues/39591)) thanks [@&#8203;arceus77-7](https://redirect.github.com/arceus77-7). - Tools/Brave web search: add opt-in `tools.web.search.brave.mode: "llm-context"` so `web_search` can call Brave's LLM Context endpoint and return extracted grounding snippets with source metadata, plus config/docs/test coverage. ([#&#8203;33383](https://redirect.github.com/openclaw/openclaw/issues/33383)) Thanks [@&#8203;thirumaleshp](https://redirect.github.com/thirumaleshp). - CLI/install: include the short git commit hash in `openclaw --version` output when metadata is available, and keep installer version checks compatible with the decorated format. ([#&#8203;39712](https://redirect.github.com/openclaw/openclaw/issues/39712)) thanks [@&#8203;sourman](https://redirect.github.com/sourman). - CLI/backup: improve archive naming for date sorting, add config-only backup mode, and harden backup planning, publication, and verification edge cases. ([#&#8203;40163](https://redirect.github.com/openclaw/openclaw/issues/40163)) Thanks [@&#8203;gumadeiras](https://redirect.github.com/gumadeiras). - ACP/Provenance: add optional ACP ingress provenance metadata and visible receipt injection (`openclaw acp --provenance off|meta|meta+receipt`) so OpenClaw agents can retain and report ACP-origin context with session trace IDs. ([#&#8203;40473](https://redirect.github.com/openclaw/openclaw/issues/40473)) thanks [@&#8203;mbelinky](https://redirect.github.com/mbelinky). - Tools/web search: alphabetize provider ordering across runtime selection, onboarding/configure pickers, and config metadata, so provider lists stay neutral and multi-key auto-detect now prefers Grok before Kimi. ([#&#8203;40259](https://redirect.github.com/openclaw/openclaw/issues/40259)) thanks [@&#8203;kesku](https://redirect.github.com/kesku). - Docs/Web search: restore $5/month free-credit details, replace defunct "Data for Search"/"Data for AI" plan names with current "Search" plan, and note legacy subscription validity in Brave setup docs. Follows up on [#&#8203;26860](https://redirect.github.com/openclaw/openclaw/issues/26860). ([#&#8203;40111](https://redirect.github.com/openclaw/openclaw/issues/40111)) Thanks [@&#8203;remusao](https://redirect.github.com/remusao). - Extensions/ACPX tests: move the shared runtime fixture helper from `src/runtime-internals/` to `src/test-utils/` so the test-only he

[AI Agent] Master Tracking: Complete AI Agent Implementation

## 🎯 Goal Track the complete implementation of autonomous Python AI Agent for CoffeeOrderSystem. --- ## 📋 Implementation Steps ### Phase 1: Infrastructure (Week 1) - [ ] **Step 1:** Setup Python AI Agent Service infrastructure #133 - Python service with FastAPI - Docker integration - Basic health checks - Makefile commands ### Phase 2: AI Integration (Week 1-2) - [ ] **Step 2:** Implement Cognee integration with semantic code search #134 - CogneeService with RAG search - Architecture context gathering - Entity file discovery - Integration tests - [ ] **Step 3:** Implement PlannerAgent with LangChain #135 - TaskPlan models - LangChain planning chain - Prompt templates - Plan generation and posting ### Phase 3: Code Generation (Week 2-3) - [ ] **Step 4:** Implement DevAgent for code generation #136 - GitHub file operations - Code generation prompts - Create/modify/delete operations - Branch management - [ ] **Step 5:** Implement PRAgent and workflow orchestration #137 - PR creation with rich descriptions - Workflow orchestrator - Background task processing - Complete end-to-end flow ### Phase 4: Advanced Features (Week 3-4) - [ ] **Step 6:** Add learning/memory system - Store successful patterns in Cognee - Learn from PR reviews - Avoid failed patterns - Improve over time - [ ] **Step 7:** Add GitHub webhook listener - Auto-trigger on issue label - Real-time processing - Queue management - Concurrent task handling --- ## 🎯 Success Criteria ### MVP (Minimum Viable Product) - ✅ Agent creates plans for issues - ✅ Agent generates compilable code - ✅ Agent creates PRs with descriptions - ✅ Works for simple tasks (add field, update config) - ✅ Error handling with GitHub notifications ### Production Ready - ☐ Handles complex multi-layer changes - ☐ Learns from successful PRs - ☐ Automatic triggering via webhooks - ☐ Rate limiting and queue management - ☐ Comprehensive test coverage (>80%) - ☐ Monitoring and metrics --- ## 📊 Architecture Overview ``` ┌────────────────────────────────────┐ │ GitHub Issues (labeled: ai-agent) │ └───────────────┬────────────────────┘ │ ↓ (webhook or manual trigger) ┌───────────────┼────────────────────┐ │ WorkflowOrchestrator │ └───────────────┬────────────────────┘ │ ┌────────┼────────┐ │ │ │ ↓ ↓ ↓ PlannerAgent DevAgent PRAgent │ │ │ │ │ │ ┌───┼───┐ │ ┌───┼───┐ │ │ │ │ │ │ │ ↓ ↓ ↓ ↓ ↓ ↓ ↓ Cognee LLM GitHub GitHub (RAG) (GPT-4) (API) ``` ### Component Responsibilities **PlannerAgent:** - Analyzes GitHub issue - Searches codebase via Cognee - Creates structured TaskPlan - Posts plan as issue comment **DevAgent:** - Generates code via LLM - Creates/modifies/deletes files - Commits to feature branch - Preserves code style **PRAgent:** - Creates pull request - Writes comprehensive PR description - Links to original issue - Adds testing checklist **WorkflowOrchestrator:** - Coordinates all agents - Handles errors - Posts progress updates - Manages background execution --- ## 📦 Tech Stack ### Core - **Python 3.11+** - Agent runtime - **FastAPI** - Web framework - **LangChain** - LLM orchestration - **OpenAI GPT-4** - Code generation - **PyGithub** - GitHub API client ### AI/ML - **Cognee** - RAG and semantic search - **OpenAI Embeddings** - Vector search - **LangChain Chains** - Prompt management ### Infrastructure - **Docker** - Containerization - **PostgreSQL** - Shared with .NET API - **uvicorn** - ASGI server --- ## 📝 Usage Example ### 1. Create Issue ```markdown Title: Add loyalty points to Customer Labels: ai-agent, enhancement Description: Add LoyaltyPoints field (int, default 0) to Customer entity. Requirements: - Update Domain/Entities/Customer.cs - Update Application/DTOs/CustomerDto.cs - Create EF Core migration - Add unit tests ``` ### 2. Trigger Agent ```bash make agent-process # Enter issue number: 138 ``` ### 3. Monitor Progress Issue comments show: ``` 🤖 AI Agent Started Phase 1/3: Analyzing task... 🤖 Execution Plan Summary: Add LoyaltyPoints field to Customer entity Steps: 1. MODIFY Domain/Entities/Customer.cs 2. MODIFY Application/DTOs/CustomerDto.cs 3. CREATE Migration file 4. CREATE Test file 🛠️ Phase 2/3: Generating code (4 files)... ✅ Step 1/4: modify Customer.cs ✅ Step 2/4: modify CustomerDto.cs ... 📦 Phase 3/3: Creating pull request... 🤖 Pull Request Created: #139 Branch: ai-agent/issue-138 Ready for review! ``` ### 4. Review PR PR includes: - Closes #138 - Comprehensive description - File changes summary - Testing checklist - Risk assessment ### 5. Merge Agent learns from successful merge for future tasks. --- ## 🧪 Testing Strategy ### Unit Tests - Agent logic (plan parsing, code generation) - Service mocks (GitHub, Cognee) - P

We Need to Stop Listening to Tony Blair Once and for All

 It might feel like months, but we’re just over a week into the US and Israel’s illegal assault on Iran, and there’s no end in sight. What is in sight, though, is [the apocalyptic vision of Tehran ablaze](https://time.com/7383099/iran-news-oil-strikes-tehran/), wreathed in thick smoke as black oil-soaked rain falls on its inhabitants. That’s the result of Israeli strikes on several oil storage depots in the city, reportedly sending burning petroleum running through gutters while [geysers of flaming gas exploded](https://www.telegraph.co.uk/world-news/2026/03/08/rivers-of-fire-in-tehran-after-oil-depots-blown-up/) from the streets. A nightmare? For most of us, yes. But for former British prime minister Tony Blair it’s apparently a dream. One that he might have liked the entire British public to be non-consensually forced into realising for him. And [not for the first time](https://www.bbc.co.uk/news/uk-politics-36701854). Were my hands bloodied with the [deaths of up to a million people](https://www.abc.net.au/news/2008-01-31/million-iraqis-dead-since-invasion-study/1028878), I’d probably think twice before giving my opinion on yet another illegal US adventure in the Middle East. Not our Tone, though. On Sunday [the papers reported](https://www.dailymail.co.uk/news/article-15623903/Tony-Blair-rebukes-Keir-Starmer-not-backing-Trump-Iran.html) that the man who told George W. Bush in the months before the disastrous Iraq war, “[I will be with you, whatever](https://www.theguardian.com/uk-news/2016/jul/06/with-you-whatever-tony-blair-letters-george-w-bush-chilcot)”, is still singing the same old tune. “We should,” Blair [told a private Jewish News event](https://www.independent.co.uk/news/uk/home-news/blair-starmer-trump-war-iran-labour-b2934207.html) on Friday night, “Have backed America from the very beginning”. That was a direct criticism of current prime minister Keir Starmer, who, [to a chorus of warmonger criticism](https://www.bbc.co.uk/news/articles/c05v28eqjyvo), initially refused the US and Israel access to British military infrastructure to launch its war on Iran. But it’s not like we’ve stayed completely out of the mess: our bases are now free for use by US jets for “defensive” actions – whatever that means – with American bombers [already touching down](https://www.theguardian.com/world/2026/mar/07/us-bomber-lands-in-uk-after-warning-of-surge-in-strikes-on-iran). Now, nobody was ever supposed to know that a former Labour prime minister so openly rubbished the current one in public. That’s because the event was conducted under Chatham House rules. In short, that means what’s said in the room can be made public, but not who said it. In long, it means elites are emboldened to express their heart’s true desires without any threat of accountability. We can’t know what was in Tony Blair’s heart when he mourned the fact that the UK was not more involved in blasting a hole straight through the security of the hundreds of millions who live in the Middle East. Nor can we tell for sure, as global oil prices [surge above $100 a barrel](https://www.bbc.co.uk/news/articles/c79542n0grwo) for the first time since the Russian invasion of Ukraine, how little the lives of Brits, long blighted by a cost of living crisis, matter to him. We can, though, look at his record. And what that shows – in my opinion – is a tendency, previously expressed via his businesses and [nowadays his Tony Blair Institute](https://www.ft.com/content/bcf1f1f5-a38f-4078-98f8-ab1ff7378895), to see fatal discord as fiscal opportunity. [Autocracy](https://www.theguardian.com/politics/2023/aug/12/tony-blair-institute-continued-taking-money-from-saudi-arabia-after-khashoggi), [oligarchy](https://www.theguardian.com/world/2022/jan/06/how-tony-blair-advised-former-kazakh-ruler-after-2011-uprising), [calamity](https://www.theguardian.com/politics/2025/jul/07/tony-blair-thinktank-worked-with-project-developing-trump-riviera-gaza-plan)? Roll up, roll up: the Blair pitch project is in town, and it has some consultancy to sell. Now, none of that is a crime. But you might think it indicates a conflict when wading into affairs of state. Blair is alleged to have form here too: in 2014, a number of former ambassadors and MPs [called for his resignation](https://www.theguardian.com/politics/2014/jun/27/tony-blair-conflict-interests-middle-east) as Middle East peace envoy for the Quartet (made up of the United Nations, the US, the EU and Russia). They claimed he was ineffective, while others noted [the growth of his business interests in the region](https://www.independent.co.uk/voices/tony-blair-uae-middle-east-envoy-qatar-israel-palestine-foreign-office-a7894641.html). Blair’s [financial arrangements](https://www.telegraph.co.uk/news/poli

Weekly Rules Review: 2026-03-09

## Weekly Rules Documentation Review - 2026-03-09 ### Overall Health Assessment The rules documentation is in **good shape overall**. All 11 rule files are relevant, and the vast majority of file paths and code patterns they reference still exist in the codebase. Two files need minor updates, and one has a moderate accuracy issue. --- ### Audit Results #### AGENTS.md **Status**: Keep **Reasoning**: Core agent guide is accurate and well-structured. The rules index table, project setup instructions, pre-commit checks, and general guidance are all current. References to `npm run ts`, `tsgo`, TanStack Router, and Base UI are correct. --- #### rules/electron-ipc.md **Status**: Keep **Reasoning**: High-value, comprehensive guide. All referenced file paths exist (`src/ipc/contracts/core.ts`, `src/ipc/types/*.ts`, `src/ipc/handlers/base.ts`, `src/lib/queryKeys.ts`). The `pendingStreamChatIds` pattern still exists in `useStreamChat.ts`. The `writeSettings` shallow merge warning is still relevant (confirmed by recent fix in commit ef4ec84 preventing stale settings reads). --- #### rules/local-agent-tools.md **Status**: Keep **Reasoning**: Concise and accurate. `modifiesState` flag is actively used across many tool files. `buildAgentToolSet` exists in `tool_definitions.ts`. `handleLocalAgentStream` exists in `local_agent_handler.ts` with `readOnly`/`planModeOnly` guards confirmed. `todo_persistence.ts` exists. `fs.promises` guidance remains relevant for Electron main process. --- #### rules/e2e-testing.md **Status**: Needs Update **Reasoning**: Mostly accurate and high-value, but has two inaccuracies in helper method references. **Issues Found**: - Lines 64-75: References `po.clearChatInput()` and `po.openChatHistoryMenu()` as methods on PageObject directly, but they actually live on the `chatActions` sub-component: `po.chatActions.clearChatInput()` and `po.chatActions.openChatHistoryMenu()`. This contradicts the sub-component pattern documented earlier in the same file (lines 29-43). **Suggested Changes**: - Update the Lexical editor section examples to use `po.chatActions.clearChatInput()` and `po.chatActions.openChatHistoryMenu()` instead of `po.clearChatInput()` and `po.openChatHistoryMenu()` --- #### rules/git-workflow.md **Status**: Keep **Reasoning**: Comprehensive and high-value. Contains many hard-won learnings about fork workflows, `gh pr create` edge cases, GitHub API workarounds, and rebase conflict resolution patterns. The `GITHUB_TOKEN` workflow chaining limitation and the `--input` pattern for special characters are particularly valuable. Recent commits (51fc07e - GitHub App tokens) confirm this area is actively evolving. **Note**: This is the longest rules file (123 lines). Some of the very specific rebase conflict tips (React component wrapper conflicts, refactoring conflicts) may be overly situational, but they're low-cost to keep. --- #### rules/base-ui-components.md **Status**: Keep **Reasoning**: All referenced component files exist (`context-menu.tsx`, `tooltip.tsx`, `accordion.tsx`). `@base-ui/react` is in the project dependencies. The TooltipTrigger `render` prop guidance and Accordion API differences from Radix are high-value patterns that prevent common mistakes. --- #### rules/database-drizzle.md **Status**: Keep **Reasoning**: Short and high-value. `drizzle/meta/_journal.json` exists. Migration conflict resolution guidance is important for rebase workflows. --- #### rules/typescript-strict-mode.md **Status**: Keep **Reasoning**: All references verified. `tsconfig.app.json` confirms ES2020 target with `lib: ["ES2020"]`. The `tsgo` installation note (Go binary, not npm package) and `response.json()` returning `unknown` are valuable gotchas. Node.js >= 24 requirement is noted. --- #### rules/openai-reasoning-models.md **Status**: Needs Update **Reasoning**: The core concept is still valid - orphaned reasoning parts are still filtered in `src/ipc/utils/ai_messages_utils.ts`. However, the specific function name referenced is outdated. **Issues Found**: - References `filterOrphanedReasoningParts()` as a named function, but this logic was refactored into the `cleanMessage()` function (inline filtering within that function). The named export no longer exists. **Suggested Changes**: - Update the reference from `filterOrphanedReasoningParts()` to describe the filtering logic within `cleanMessage()` in `src/ipc/utils/ai_messages_utils.ts` --- #### rules/adding-settings.md **Status**: Keep **Reasoning**: All file paths verified: `UserSettingsSchema` in `src/lib/schemas.ts`, `DEFAULT_SETTINGS` in `src/main/settings.ts`, `SETTING_IDS` in `src/lib/settingsSearchIndex.ts`, `AutoApproveSwitch.tsx` as template. Recent commit d6ab829 (add max tool call steps setting) confirms this pattern is actively used. --- #### rules/chat-message-indicators.md **Status**: Keep **Reasoning**: Short (12 lines), low token cost. `dyad-status` tag implementation confirmed in

Weekly Report Mar 2 -- Mar 9, 2026

# Weekly Report: Mar 2 -- Mar 9, 2026 ## Quick Stats | Metric | Count | |--------|-------| | Merged PRs | 47 | | Open PRs | 24 (11 draft) | | Open issues | 61 | | New issues this week | 33 | | Issues closed this week | 6 | | CI runs on main | 30 | ## Highlights An exceptionally active week with 47 merged PRs. Key themes: - **Realm migration**: Keycloak master-to-kagenti realm migration landed (#764), with follow-up fixes (#851, #863) - **Platform hardening**: Podman support (#861), Docker Hub rate limit fixes (#844), PostgreSQL mount fix (#852) - **CI/CD improvements**: OpenSSF Scorecard 7.1->8+ (#807), stale workflow permissions (#859), HyperShift cluster auto-cleanup (#854) - **New capabilities**: CLI/TUI for Kagenti (#835), Istio trace export to OTel (#795), RHOAI 3.x integration (#809) - **Dependency updates**: 8 Dependabot PRs (Docker actions major bumps, CodeQL, Trivy) - **Authorization epic**: 7 new issues (#787-#794) laying out a comprehensive authorization and policy framework - **Agent sandbox epic**: New epic (#820) for platform-owned sandboxed agent runtime ## Issue Analysis ### Epics (active initiatives) | # | Title | Owner | Status | |---|-------|-------|--------| | #862 | AgentRuntime CR — CR-triggered injection | @cwiklik | New, design phase | | #820 | Platform-Owned Sandboxed Agent Runtime | @Ladas | Active, PR #758 in progress | | #828 | Migrate installer from Ansible/Helm to Operator | @pdettori | New, planning | | #787 | Authorization, Policies, and Access Management | @mrsabath | New, 6 sub-issues filed | | #841 | Org-wide orchestration: CI, tests, security | @Ladas | Active, PRs #866-#868 open | | #767 | Migrate from Keycloak master realm | @mrsabath | Mostly done (#764 merged), close candidate | | #619 | Tracing observability PoC | @evaline-ju | Active (#795 merged) | | #621 | OpenSSF Scorecard to 10/10 | @Ladas | Active (#807 merged, now 8+) | | #523 | Refactor APIs for Compositional Architecture | @pdettori | Active, PR #770 open | | #518 | OpenShift AI deployment issues | @Ladas | Active (#809 merged) | | #309 | Full Coverage E2E Testing | @cooktheryan | Ongoing | | #440 | Multi-Team Deployment on RHOAI | @Ladas | Ongoing | | #439 | Namespace-Based Token Usage Quotas | @Ladas | Ongoing | | #614 | Feedback review community meeting | @Ladas | Stale (>30d no update) | | #623 | Identify Emerging Agentic Deployment Patterns | @kellyaa | Stale | | #612 | Agent Attestation Framework | @mrsabath | Stale, PR #613 still draft | ### Security-Adjacent Issues | # | Title | Status | Recommendation | |---|-------|--------|----------------| | #822 | Keycloak configmap should be secret | Open | High priority — credentials in configmap | | #106 | Replace hardcoded secret with SPIRE identity | Open | Long-standing, PR #769 in draft | | #333 | SPIFFE ID missing checks | Open | Stale, needs triage | | #267 | Replace hard-coded Client Secret File path | Open | Good first issue, needs assignee | ### Bug Reports | # | Title | Still affects main? | PR exists? | Recommendation | |---|-------|---------------------|------------|----------------| | #856 | Warnings during Kagenti install | Likely yes | No | Triage — install warnings | | #855 | Can't checkout source on Windows | Yes (skill naming) | PR #869 | In progress | | #829 | Deleting A2A agent doesn't delete HTTPRoute | Likely yes | No | Needs fix | | #826 | No way to log out of Kagenti | Yes | No | UX bug, needs fix | | #825 | Build failures lead to stuck state | Likely yes | No | Needs investigation | | #738 | UI drops spire label on 2nd deploy | Likely yes | No | Stale (>30d) | | #486 | Installer issues (Postgres/Phoenix) | Partially (#852 fixed PG) | Partial | Re-verify Phoenix | | #781 | kagenti-deps fails on OCP 4.19 | Unknown | No | Stale, needs triage | | #606 | Unsupported Helm version | Unknown | No | Stale, needs triage | | #655 | Duplicated resources between repos | Unknown | No | Stale, needs triage | ### Issues Closed This Week (good velocity) | # | Title | Fix PR | |---|-------|--------| | #833 | UI login fails after realm migration | #834 | | #831 | --preload fails when images cached | #832 | | #819 | Remove deprecated Component CRD refs | #818 | | #813 | Import env vars references bad URL | #821 | | #810 | Import env vars silently fails on dup | #821 | | #804 | OAuth secret job SSL error on OCP | #805 | ### Feature Requests | # | Title | Priority | Recommendation | |---|-------|----------|----------------| | #858 | Use new URL for fetching Agent Cards | Medium | Good first issue | | #836 | AuthBridge sidecar opt-out controls in UI | Medium | Tied to #862 epic | | #824 | Help text for UI fields | Low | Good UX improvement | | #823 | Examples as suggestions in UI | Low | Nice-to-have | | #817 | Auto-add issues/PRs to project board | Medium | PR #870 open | | #814 | Mechanism to update agent via K8s | Medium | Operator feature | | #786 | Register MCP servers from UI | Medium | UI feature | | #783 | Agent card signing/verifica

We Need to Stop Listening to Tony Blair Once and for All

 It might feel like months, but we’re just over a week into the US and Israel’s illegal assault on Iran, and there’s no end in sight. What is in sight, though, is [the apocalyptic vision of Tehran ablaze](https://time.com/7383099/iran-news-oil-strikes-tehran/), wreathed in thick smoke as black oil-soaked rain falls on its inhabitants.  That’s the result of Israeli strikes on several oil storage depots in the city, reportedly sending burning petroleum running through gutters while [geysers of flaming gas exploded](https://www.telegraph.co.uk/world-news/2026/03/08/rivers-of-fire-in-tehran-after-oil-depots-blown-up/) from the streets. A nightmare? For most of us, yes. But for former British prime minister Tony Blair it’s apparently a dream. One that he might have liked the entire British public to be non-consensually forced into realising for him. And [not for the first time](https://www.bbc.co.uk/news/uk-politics-36701854). Were my hands bloodied with the [deaths of up to a million people](https://www.abc.net.au/news/2008-01-31/million-iraqis-dead-since-invasion-study/1028878), I’d probably think twice before giving my opinion on yet another illegal US adventure in the Middle East. Not our Tone, though. On Sunday [the papers reported](https://www.dailymail.co.uk/news/article-15623903/Tony-Blair-rebukes-Keir-Starmer-not-backing-Trump-Iran.html) that the man who told George W. Bush in the months before the disastrous Iraq war, “[I will be with you, whatever](https://www.theguardian.com/uk-news/2016/jul/06/with-you-whatever-tony-blair-letters-george-w-bush-chilcot)”, is still singing the same old tune.  “We should,” Blair [told a private Jewish News event](https://www.independent.co.uk/news/uk/home-news/blair-starmer-trump-war-iran-labour-b2934207.html) on Friday night, “Have backed America from the very beginning”. That was a direct criticism of current prime minister Keir Starmer, who, [to a chorus of warmonger criticism](https://www.bbc.co.uk/news/articles/c05v28eqjyvo), initially refused the US and Israel access to British military infrastructure to launch its war on Iran. But it’s not like we’ve stayed completely out of the mess: our bases are now free for use by US jets for “defensive” actions – whatever that means – with American bombers [already touching down](https://www.theguardian.com/world/2026/mar/07/us-bomber-lands-in-uk-after-warning-of-surge-in-strikes-on-iran). Now, nobody was ever supposed to know that a former Labour prime minister so openly rubbished the current one in public. That’s because the event was conducted under Chatham House rules. In short, that means what’s said in the room can be made public, but not who said it. In long, it means elites are emboldened to express their heart’s true desires without any threat of accountability.  We can’t know what was in Tony Blair’s heart when he mourned the fact that the UK was not more involved in blasting a hole straight through the security of the hundreds of millions who live in the Middle East. Nor can we tell for sure, as global oil prices [surge above $100 a barrel](https://www.bbc.co.uk/news/articles/c79542n0grwo) for the first time since the Russian invasion of Ukraine, how little the lives of Brits, long blighted by a cost of living crisis, matter to him. We can, though, look at his record. And what that shows – in my opinion – is a tendency, previously expressed via his businesses and [nowadays his Tony Blair Institute](https://www.ft.com/content/bcf1f1f5-a38f-4078-98f8-ab1ff7378895), to see fatal discord as fiscal opportunity. [Autocracy](https://www.theguardian.com/politics/2023/aug/12/tony-blair-institute-continued-taking-money-from-saudi-arabia-after-khashoggi), [oligarchy](https://www.theguardian.com/world/2022/jan/06/how-tony-blair-advised-former-kazakh-ruler-after-2011-uprising), [calamity](https://www.theguardian.com/politics/2025/jul/07/tony-blair-thinktank-worked-with-project-developing-trump-riviera-gaza-plan)? Roll up, roll up: the Blair pitch project is in town, and it has some consultancy to sell.  Now, none of that is a crime. But you might think it indicates a conflict when wading into affairs of state. Blair is alleged to have form here too: in 2014, a number of former ambassadors and MPs [called for his resignation](https://www.theguardian.com/politics/2014/jun/27/tony-blair-conflict-interests-middle-east) as Middle East peace envoy for the Quartet (made up of the United Nations, the US, the EU and Russia). They claimed he was ineffective, while others noted [the growth of his business interests in the region](https://www.independent.co.uk/voices/tony-blair-uae-middle-east-envoy-qatar-israel-palestine-foreign-office-a7894641.html).  Blair’s [financial arrangements](https://www.telegraph.co.uk/news