U G Murthy @murthyug
building adaptiveagent https://t.co/tNC5wTAiia torunforever.wordpress.com ÜT: 12.887904,77.542893 Joined May 2009-
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🥳 Excited to start revealing what we've been working on in the last few months. First, we decided to reinvent Kubernetes for agentic workloads with statefulness and fast resumption. Secondly, we are building an agentic orchestrator that will be Google's open agentic orchestrator and runtime. github.com/google/ax
@AmpCode @sqs 5/5: @AmpCode, The goal is neither to micromanage agents nor trust them blindly. Give them autonomy over implementation while retaining authority over evidence, acceptance, and release. #learnings #codingagent
@AmpCode @sqs 4/5: @AmpCode, Move durable context out of chat and into maintained artifacts: plans, decisions, acceptance criteria, and progress records. This enables shorter prompts without sacrificing clarity or control. #learnings #codingagent
@ampcode, @sqs, I have been using amp for a year now and have seen it change overtime. I was also curious as how it has changed me? Especially in the way I have been interacting with amp. So I ask Puck to analyse my threads since Sept 2025 and come up with what it observed as set of X posts, presented below without any changes
@suneelkoyi All the best. Consistency beats anything in all fields. Keep it going.
2/4 : What you send / what you get You send: - State — ticket, email, JSON, policy, agent output - Questions — mix in one call Choice = pick from your list Score = rate on your rubric Noul = P(statement is true) You get: - chosen option + distribution + confidence - score - yes-probability 0–1 No prose to parse. No extra category outside the schema.
1/4: Judge, don’t generate. Jev is not a ChatGPT replacement. LLMs write: code, emails, plans, patches. Jev judges: Choice / Score / Noul. It does not generate text or code. TypeSafe says forcing it to “write” by chaining choices is slow and bad.Use it as a typed judge next to a generator. Your code still owns the "if" typesafe.ai
Another Jev based usecase. x.com/murthyug/statu…
Breaking: Browser Use + Jev = Ultrafast ⚡ Findings flights took 7s and cost only $0.0039 🤯 > new action space every step > DOM state space > small LLM fallback to type (this video is at 1x speed btw) Built a tiny open source browser agent. try it below ↓
4/4 : Use Cases Pattern: - LLM (or template, or human) produces. - Jev scores and routes. - Code acts. Some use cases - Ticket / email routing: queue, LLM, or human - Agent gates: which tool/skill, continue / retry / stop / ask - Guardrails: jailbreak, PII, policy, bad tool call - Model router: cheap model vs expensive vs human - RAG: score / rerank passages - Semantic lint: “does this PR touch auth with no tests?” - Batch classify a corpus - Real-time loops: pick among allowed actions
3/4 : Cost as a judge Faster & Cheaper - Jev list price: $0.042 / million input tokens. Output tokens free. - about 194x faster as per typesafe.ai
@sqs @AmpCode @hameonline ampcode.com/news/one-runne… Thank you
@AmpCode @sqs I switched from TUI to Desktop App today. I am in the process of build a macos app. My usual process was - start and orb, with a local runner for compile/test/proofs and was hoping macos app would have fired a local runner instead of me doing it. The amp app checked for a local runner but I had to start it manually - next time I will try asking instead of expecting it to do on its own.
@thorstenball Glad to hear this. Kudos to you and team for relentless in pushing the frontier
@CompleteSkeptic Joined the waitlist but the form is no longer available...Would have loved to try out on my new agent ugmurthy.github.io/adaptive-agent…
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