Best of Automation — February 2026

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    Article
    Avatar of vibecodingVibe Coding·15w

    How Peter Steinberger Ships at 10x Speed

    Peter Steinberger, creator of OpenClaw and former PSPDFKit founder, shares his approach to building at exceptional speed using AI coding agents. His methodology centers on running 5-10 agents in parallel across separate git checkouts, using Gemini for spec generation and Claude Codex for implementation. He advocates for CLI tools over MCPs for composability, emphasizes closing verification loops so agents can self-correct, and positions humans as the "taste layer" providing vision while agents handle execution. Key insights include avoiding over-engineered AI tooling, using voice input over typing, validating locally before merging, and treating user feedback from Discord as direct feature requests. He built 43 projects before achieving viral success, demonstrating that shipping constantly and learning from failures is essential.

  2. 2
    Video
    Avatar of fireshipFireship·14w

    7 AI updates breaking the SaaS business model...

    Recent AI developments are threatening the traditional SaaS business model as major software companies lost $1 trillion in market cap. Seven key AI releases demonstrate this shift: OpenAI's Codex app and 5.3 model, Claude's Opus 4.6, Alibaba's Qwen 3 Coder Next, ZAI's GLM5, Minimax M2.5, GitHub Agent HQ, and Waymo's world model. These tools enable AI agents to replace multiple human seats, offer open-weight alternatives to expensive subscriptions, and automate entire development workflows. The core thesis: when AI intelligence becomes abundant and cheap, the per-seat pricing model that drives SaaS profit margins becomes obsolete.

  3. 3
    Article
    Avatar of claudeClaude·15w

    How Anthropic uses Claude in Marketing

    A non-technical growth marketer at Anthropic used Claude Code to build custom automation workflows that reduced ad creation time from 30 minutes to 30 seconds. Starting with zero coding experience, he created a Figma plugin for generating ad variations and a Google Ads copy workflow with CSV export. The article details his process, best practices for non-technical users building with AI coding tools, and examples of how other marketing teams at Anthropic are using Claude to save hundreds of hours monthly on repetitive tasks.

  4. 4
    Article
    Avatar of hordeHorde·13w

    Here's how I use OpenClaw agents daily

    A developer shares their personal daily workflow using OpenClaw AI agents across a wide range of tasks: coding and code review, email scanning and invoice organization, trend monitoring from X/HN/Reddit/ProductHunt every two hours, content idea generation for YouTube and social media, sponsorship proposal handling, marketing and product sharing on awesome repos, cold outreach, Discord management, workout/nutrition planning, follow-up reminders, daily project improvement suggestions, and self-updating agents. The setup also features smart model selection to optimize results at the lowest cost.

  5. 5
    Video
    Avatar of codinggopherThe Coding Gopher·16w

    Meta now has the most insane AI agent

    Meta's AI agent represents a shift from large language models to large action models (LAMs) that can interact with computers through visual understanding and mouse/keyboard control. The system uses vision transformers to parse screen pixels, DOM annotation for web interaction, and operates in ephemeral sandboxed microVMs for security. By working at the UI layer rather than requiring APIs, it enables probabilistic automation of complex workflows across legacy systems, marking a transition from text-to-text models to multimodal input-to-executable-action systems.

  6. 6
    Article
    Avatar of workchroniclesWork Chronicles·15w

    (comic) Why AI Won't Replace Everyone

    A comic exploring why AI won't completely replace human workers, presented through visual storytelling. The piece uses humor to address common concerns about AI's impact on employment in the tech industry.

  7. 7
    Article
    Avatar of reidburkeReid Burke·15w

    Something Big Is Happening

    AI capabilities have reached an inflection point where models can now autonomously complete complex, multi-hour tasks and even contribute to building newer versions of themselves. Recent releases like GPT-5.3 Codex and Claude Opus 4.6 demonstrate judgment-like decision-making that eliminates the need for human oversight in many knowledge work tasks. Industry leaders predict 50% of entry-level white-collar jobs could be eliminated within 1-5 years as AI becomes a general substitute for cognitive work across law, finance, medicine, software engineering, and other fields. The author urges immediate adoption of paid AI tools, daily experimentation, and financial preparation, emphasizing that the window to gain competitive advantage by being early is closing rapidly.

  8. 8
    Article
    Avatar of ramp_engRamp Engineering·13w

    We fixed ~100 security issues in 6 days with 0 humans

    Ramp's security engineering team built a multi-agent pipeline that autonomously found, validated, and patched nearly 100 security vulnerabilities in their backend codebase in under a week, with no human involvement until PR review. The system used specialized detector agents for specific vulnerability classes (e.g., IDOR), adversarial manager agents to filter false positives (rejecting 40% of initial findings), a validator agent that wrote integration tests to confirm real issues, and a fixer agent that applied patches using test-driven development. The approach uncovered novel high-severity issues missed by penetration testing, bug bounties, and 10+ commercial scanning tools. The entire setup required only a four-hour hackathon and one week of work by a single engineer.

  9. 9
    Article
    Avatar of swizecswizec.com·15w

    The 3 curves that make a scalable business

    Building scalable businesses requires managing three growth curves: exponential growth in users and revenue through retention, linear growth in bugs as usage increases, and logarithmic growth in support work through automation and tooling. Engineers create value by building systems that maintain these curves through code quality, automation, documentation, and reducing operational overhead. Many startups fail not from lack of features, but from inability to scale operations to match demand.

  10. 10
    Article
    Avatar of dhhDavid Heinemeier Hansson·15w

    Clankers with claws

    OpenClaw enables AI models to operate persistently with their own machine, memory, and execution environment beyond simple prompt-response cycles. Testing shows modern AI agents can navigate human-centric digital interfaces without specialized tools, APIs, or MCPs—successfully signing up for services, managing email, and completing multi-step tasks autonomously. This demonstrates that AI agents may soon interact with software through standard user interfaces rather than requiring dedicated machine-readable protocols.

  11. 11
    Article
    Avatar of staabmMarkus Staab·15w

    Automate the process to find a regression commit

    Git bisect can be automated using the `git bisect run` command to find regression commits without manual intervention. The process involves creating a test script that returns exit code 0 for expected behavior and non-0 for failures, then running `git bisect run ./test.sh` to automatically identify the first bad commit. This eliminates human error and saves time compared to manually testing each commit during bisection.

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