1LittleCoder💻
21K posts
@1littlecoder
developers & builders @nebiustf - Educator at https://t.co/BBKhRY0mTN Opinions are ChatGPTs
UPDATE: Came up with an even better version of this prompt after the feedback Ask Codex to look across your sessions, Memories, and Chronicle, identify patterns, reuse what already exists, and only create the smallest useful skill, subagent, or automation. "Look back over my recent work from the last 30 days, or all available history if shorter, and identify repeated manual workflows worth packaging. Use available evidence in this order: - Recent Codex sessions and task summaries. - Codex Memories and rollout summaries to find patterns repeated across sessions. - Chronicle, if enabled, to spot repeated work outside Codex. Use Chronicle for discovery only; confirm important details in the relevant source system when possible. - Existing skills, custom agents, and automations, so you reuse or extend what already exists instead of duplicating it. Look broadly for work that is repeated, time-consuming, error-prone, context-heavy, or benefits from a consistent process. Include workflows across coding, research, writing, planning, communication, operations, analysis, and personal administration. Only act on a candidate when it: - occurred at least twice, or is clearly likely to recur and costly to repeat; - has stable inputs, a repeatable procedure, and a clear output or stopping condition; - would materially improve speed, quality, consistency, or reliability; - is not already adequately covered. Choose the smallest appropriate form: - Skill: a reusable workflow or playbook. - Custom subagent: a bounded specialist role or investigation task suitable for delegation. - Automation: a scheduled or recurring check, report, reminder, or monitor. - Skip: work that is too one-off, ambiguous, sensitive, or poorly evidenced to package. First produce a compact shortlist with: - repeated workflow - supporting evidence and dates - frequency/confidence - recommended form: skill, subagent, automation, extend existing, or skip - why it is or is not worth creating Then create only the high-confidence missing items. Keep them narrow, practical, source-aware, and easy to validate. Do not create speculative, overlapping, or overly broad assets. Finish with: - what you created or extended - what you deliberately skipped - what needs more evidence before packaging"
Google gemini’s omni will change AI motion graphics forever! In today’s @aiweekendsxyz hack in the afternoon build, I demoed what we can currently do and how things will change once omni’s API releases! Thanks @dasritav , @0xratnakar and team for enabling it!
we upgraded to a bigger villa in Da Nang 🇻🇳 opening 2 more spots. 30 days. 12 builders. Vietnam. 📍 just $400/person for stay. starts July 1st. who’s in?
TLMs: Tiny LLMs and Agents on Edge Devices with @cormacb youtube.com/watch?v=-TiET_… Function Gemma ships at 270 million parameters and runs nearly 2,000 tokens per second prefill on a Pixel 7. Out of the box, it hits 46% accuracy on a fixed set of app intents. Fine tune on a synthetically generated dataset and that clears 90% on eight of ten functions. Cormac walks through the two paths developers have for on device AI: a skill harness built on Gemma 4 with a restaurant roulette demo running fully on device. Then Eloquent, a production transcription app built by chaining two sub billion parameter models together. cc @osanseviero
