Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming) header
Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming) profile picture

Wolven Tech: Rust consulting. AllSource Prime: durable AI memory → https://teapawt.net/t.co/CfdDxoKhs5 Longhand: AI workflows & training → https://teapawt.net/t.co/Rbml5TOtFF

London, United Kingdom
Joined January 2014
Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)Photo by Decebal | Rust for the AI execution layer ⚙️ (@ddonprogramming)
1,000 followers. Thank you. Marking it by opening something up: I am taking on fractional full stack AI developer work through Wolven Tech Ltd. Five spots. One is already taken. How it works below.
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A successful Claude request can carry a profile ID the provider never looked up. Trace one customer through a retry and a batch before adding a provider route. 1/5
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Trace a tenant through retries, batches and supported fallback routes. Compare intended identity with the outgoing profile and the platform’s checks. Attribution loss is a proposed application failure test, not a reported provider defect. 4/5
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The checkpoint hash matches. Activation precision may have changed underneath it. Before approving an inference optimisation, check which arithmetic ran. 1/5
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Retain weight format, activation format, hardware and kernel configuration. Check task outcomes on release cases and keep the qualified configuration available for rollback. A checkpoint hash leaves those execution choices unanswered. 4/5
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An engineer asks for more agent budget. What will the next attempt establish? Ask for the unresolved question and the observation that would change the decision to continue. 1/6
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Publish criteria beforehand. Review reasoning and responses to evidence across different tasks, with peer discussion. Tool spend and a lucky model answer cannot supply that judgement. This is unvalidated coaching, not an employment rubric. 5/6
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Requests keep arriving while new workers prepare. A brief scaling pause tells you little about that wait. Ask when the added workers take useful load. 1/5
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Measure trigger-to-readiness, serving interruption and queue growth separately. Repeat under the cache and storage conditions your deployment can encounter. Review reserve capacity and scaling thresholds against that evidence. 4/5
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