Notes: Defeating Non-Determinism in LLM Inference
Study notes on why LLMs produce different outputs for the same prompt—even at temperature 0—and the batch invariance solutions that achieve 100% reproducibility.
Forward deployed senior engineers. Accelerated by AI.
via Execution Analysis
// Operational History
It is optimized for billing hours, not shipping code.
Agencies burn months in "Discovery" and "Alignment" workshops. By the time an engineer writes the first line of code, your market window has shifted.
You pay senior rates for project managers, account executives, and "creative directors." The actual engineering is often handed to junior developers learning on your dime.
// Singular Activated
Just elite engineers building critical software and AI systems.
*For a low-complexity startup MVP.
We utilize DECSEA, our proprietary AI-accelerated synthesis framework. This allows two senior engineers to outpace a 10-person agency team. We skip the slides and ship the MVP.
We assemble a strike team. Every dollar of your budget goes to IC-7+ (on Google-scale) engineers who solve hard problems and write code that powers your business.
AI provides the velocity, but it requires elite engineering guidance to produce reliable software, one that becomes a long-term asset, not a temporary demo.
Frontier models are probabilistic; critical systems must be deterministic. DECSEA runs generated code in real-time execution sandboxes, verifying logic and safety before it ever touches your codebase.
We deploy pre-audited, enterprise-grade software LEGO blocks for common functionality. This allows us to focus engineering rigor on your unique IP. You get speed on Day 1, and full code ownership on Day 30.
We eliminate decision paralysis. We build on a strictly typed, hardened stack ready to be deployed in highly regulated industries. Secure by default, scalable by design.
Comparative analysis of deployment velocity, engineering rigor, and capital efficiency.
| Metric | Traditional Agency | Internal Hire | Singular |
|---|---|---|---|
| Time to Deployment | 3-6 Months |
6-9 Months
(Includes Recruiting)
| 4-12 Weeks |
| Engineering Talent |
Mixed
High variance
| Unknown |
Senior
Verified Elite
|
| Technical Debt Profile |
High / Fragile
Rewrites common post-launch
| Variable |
Zero-Debt Foundation
Modular & Scalable Day 1
|
| Capital Allocation | ~40% Overhead
PMs, Sales, Layers
|
High Fixed Cost
Salary + Equity + Benefits
| 100% Engineering |
// Validated Outcomes
"We used to spend months manually reconciling data. Now it happens instantly. In four months, Singular built a clinical intelligence platform that sped trial timelines by 40%. The clarity of AI insights is game-changing.
"I've been in deep tech for 15 years, and Singular is in a different league. Their precision and mastery were world-class. I almost want to gatekeep them for ourselves.
// Knowledge Logs
Study notes on why LLMs produce different outputs for the same prompt—even at temperature 0—and the batch invariance solutions that achieve 100% reproducibility.
We've watched companies burn seven figures on bloated teams. Here is the breakdown of why the traditional agency model is structurally designed to fail you.
Technical Protocol: A walkthrough on fine-tuning the 7B pre-trained model using the PEFT library and QLoRa method for resource-constrained environments.