The three most counterintuitive takeaways: ask for ten variations at once, stick to wireframes when details do not matter, and handle the final mile yourself.
Telemetry tracking 22,000 developers over two years shows a 66% increase in output alongside a 242.7% surge in production incidents per PR.
The median occupation has AI touching just one-fifth of its tasks, 29% of jobs show zero AI use at all, and even in cognitive work, AI carries a task start to finish only 6.5% of the time.
Eight prompts you can copy straight into your workflow — plus one counterintuitive lesson: telling a review prompt to flag only high-severity issues can genuinely make it report less.
Four internal skills work in sequence: catch bugs, clean up diffs, run the app, and double-check design specs when changes touch the UI.
The models use a brute-force approach to find code: scanning the entire repo for text matches. Generic names force them to read hundreds of extra files.
The same price now buys roughly double the score, and this release's chart plots cost on the x-axis instead of accuracy — five effort tiers let you dial in exactly how good you want the model and how much to pay for it.
Rules gave way to judgment calls and examples gave way to interfaces — one tool description shrank from roughly 9,100 characters to a single sentence and an enum.
Video access opens for application now; image generation is still weeks away, with open weights coming last. Pricing remains unannounced, and Black Forest Labs itself labels the human-evaluation results as preliminary.
His take: AI is amplifying workers rather than replacing them—killing tasks is not the same as killing jobs.
Built for customer-facing and internal workflows, Presence opens with voice and chat first—OpenAI says its own phone line already runs 75% without humans, and a Codex improvement loop cut human handoffs another 15 points in 10 days.
From AI tutors for kids to data centers built at sea — and, for the first time, a request from the sitting US Secretary of the Army.
The investor who led a $500 million Series D says Anthropic's real moat isn't the model — it's the layer that makes it usable.
Swapping the harness around the same model can double the cost, and open-source GLM 5.2 matches Opus 4.8 for 30% less per task — on a benchmark built from Databricks' own merged pull requests, so none of it is searchable online.
Anthropic open-sourced the templates and prompts behind the playbook, after a migration that burned through 5.9 billion uncached input tokens — about $165,000 at API prices.
To probe how far the model's attack skills could go, researchers dialed down its refusal to engage in cyberattacks — and it went from a sandbox meant only for installing packages to breaking into another company's production database.
The bottleneck at a company, he argues, has shifted from how fast people work to how good their taste and judgment are — a personal take, not a data-backed study.
All three are Flash models: the flagship writes two-thirds less, the cheapest tier costs 60% more instead of less, and the third is government-only.
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