Alex Nahas

Agentic Software Engineering — Pulse #2. Behavioral alignment now has its first control primitives. Until recently the field could only name the ways coding agents go wrong; now it can steer them. The sharpest result is TACT: over a long task an agent tends to drift into overthinking or overacting, and TACT finds that this drift is a single measurable signal inside the model, so you can push against it while the agent runs, with no retraining, and it resolves 5.8pp more issues. Two blunter levers join it. Symbolic guardrails enforce most explicit rules (~74%) with plain deterministic checks instead of trusting the model to follow them. And the 5,000-run Claude Code study finds that telling an agent what not to do lifts its score (+13.8pp) while telling it what to do does not; even random rules help, so it is the constraint itself doing the work, not the agent’s grasp of the advice. No single unifying mechanism yet, but the corner finally has tools… Read the full pulse 👇 https://lnkd.in/eBiaQFBh

Most people treat CLAUDE.md like a prompt file. That's the mistake. After running Claude Code across enterprise repos, the pattern is clear: the teams getting real value aren't writing better prompts — they're building better project structure. Claude Code needs 5 layers to behave like a project-native engineer: 1️⃣ CLAUDE.md — Short, focused repo memory (purpose + map + rules) 2️⃣ Skills — Reusable expert modes for common workflows 3️⃣ Hooks — Deterministic guardrails that fire automatically 4️⃣ Docs — Progressive context Claude can read on demand 5️⃣ Local CLAUDE.md — Module-specific guidance near sharp edges The critical insight: prompts are suggestions. Hooks are guarantees. When you tell Claude "always run tests after editing auth/" in a prompt, it might forget by the third edit. Wire it as a hook and it's automatic. Prompting is temporary. Structure is permanent. Full breakdown → https://lnkd.in/giamFtTM #ClaudeCode #AIEngineering #EnterpriseAI #DeveloperTools #AIAgents #Anthropic #DevEx #SoftwareEngineering

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MongoDB shareholders just got $6.4B richer after Q2 earnings - the stock popped 35% on the announcement. And the results backed it up: ARR growth: +23% YoY (vs 13% last year) CAC payback: 23 months (down from 33) Free cash flow margin: +12% (from -1%) Operating margin: -11% (improved from -15%) S&M spend: down to 41% of revenue (from 46%) They also added 434M in net new ARR over the last 12 months, with strong traction from their shift upmarket - now 2,564 customers paying $100K+ annually. A strong efficiency story + market confidence = $24B market cap at 10.5x ARR. Want more breakdowns? Click the link in the comments below. #SaaS #MongoDB #ARR #Growth #SaaSReport

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The math on "10x AI engineers" doesn't add up. 🧮 10x productivity means what took a quarter now takes 1.5 weeks. That's not just faster coding. That's 10x faster: → Code reviews → QA testing → Deployment pipelines → Stakeholder alignment The human bottlenecks haven't changed. You can't compress 3 months of back-and-forth into 7 days. The real productivity gains? Narrow bursts. Writing boilerplate. One-off scripts. Not the architectural thinking that separates senior engineers. Most "10x" claims come from: • AI startup founders (incentives matter) • Managers making engineers feel replaceable • Engineers in their honeymoon phase Been testing Claude Code, Cursor, and others for months. They're useful tools. Not productivity revolutions. Your engineering fundamentals still matter more than your prompting skills. Are you feeling pressure to become an "AI engineer"? #Engineering #AI #Productivity #SoftwareDevelopment https://lnkd.in/ewTFSrH7

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What a “10x Software Engineer” Really Is We’ve all heard the phrase “10x engineer.” It’s usually misunderstood. A 10x engineer isn’t someone who types faster, ships more lines of code, or works unsustainable hours. The real 10x multiplier comes from something far more rare—and far more valuable. 1. They create leverage, not code volume A true 10x engineer builds systems, abstractions, and tools that make everyone around them more effective. Their impact compounds through the team. 2. They have ruthless clarity They see the essence of a problem quickly—what matters, what doesn’t, and what the simplest workable solution looks like. This clarity prevents months of wasted effort. 3. They manage complexity with taste Taste is the underappreciated trait of elite engineers. It’s the instinct for clean architecture, thoughtful tradeoffs, and code that’s built to evolve, not just to work today. 4. They raise the bar by how they work Their communication is crisp. Their reviews teach, not nitpick. Their sense of ownership is contagious. They model a standard others naturally adopt. 5. They make the whole team move faster This is the real multiplier. The best engineers unlock speed across product, design, infra, and leadership by reducing uncertainty and increasing confidence in decisions. A 10x engineer isn’t a solo superhero—they’re a force amplifier. They don’t outwork the team; they elevate it.

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University of California, Berkeley CS courses required students to develop and deploy several full-stack web apps and needed sophisticated custom full-stack autograders that use industrial-strength tooling. By teaching with Codio, they're able to: 1. Ensure students avoid configuration issues like having the wrong version of the development stack 2. Easily share course materials with other instructors 3. Meet sophisticated autograding demands without spending extensive instructor time on dev-ops "We needed both a student-facing IDE that was 'ready to go' and didn't require futzing or installation on the student's part, but was also sophisticated enough to handle our autograding demands without requiring extensive instructor time spent on dev-ops or configuration." - Armando Fox, Professor of Computer Science, UC Berkeley

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🚀 Argo CD Shallow Clone Support In this short, Peter Jiang explains the newly added shallow clone capability in Argo CD — letting the repo server fetch only a limited number of commits with configurable depth. This feature helps improve performance and efficiency when working with large Git repositories. 👉 Watch here: https://lnkd.in/e5QtNQei

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