Posts

Claude Code Alternatives: A Price-Focused Guide for Engineering Teams

Compare Claude Code alternatives by price — Codex, open-source coding agents, self-hosted GPU economics, and TensorOps CodeMesh, the enterprise hybrid stack.

Agent RFT, Practical Guide

A nine-step tutorial on agent reinforcement fine-tuning (RFT): how to build the dataset, stand up tool servers, write the grader, configure KL and group size, size GPUs, and pick between TRL, verl, OpenRLHF, Unsloth, and NeMo RL — with code and example outputs at every step.

Agent Reinforcement Fine-Tuning

When prompt engineering stops being enough — a practitioner’s guide to agent reinforcement fine-tuning (RFT) for tool-using agents. What it changes, when to reach for it, and what early production results actually show.

AgentOps & LLM Observability, Explained

From opaque agent behavior to reliable, measurable performance. A field guide to AI agent observability — Job Cards, Agent Bureaucracy, and why documenting the work beats tracing LLM calls.

Building "Ask Seeking Alpha": How TensorOps and Seeking Alpha Connected Generative AI with Proprietary Data

How TensorOps built Seeking Alpha a multi-agent router and a "Grounded Autonomy" protocol that grounds GenAI on proprietary research data — minimizing hallucinations and keeping answers fresh.

LLM Mixture of Experts Explained

A 2026 field guide to Mixture of Experts: how it works, why GPT-4, DeepSeek, Llama 4, Qwen3, Mistral Large 3 and Kimi K2 all rely on it, plus Super Experts, routing strategies, and the systems trade-offs MoE forces on production teams.

How Do Sellers Set Floors in Programmatic Advertising Without Killing Win Rate?

A practical guide to setting per-request floor prices in Prebid + GAM without collapsing fill rate: where the trade-off actually lives, why static floors burn demand, and how session-aware FPO lifts revenue per request.

How to Train a Custom LLM for Your Business in 2026

The four-stage pipeline — domain-adaptive continued pre-training, LoRA SFT, online DPO, and rejection-sampled SFT — for turning a strong open base model into a domain-specialized LLM, with the hyperparameters and trade-offs that actually matter.

State of AI for Organizations

An opinion piece from TensorOps on what enterprise AI actually looks like in 2026 — three years after ChatGPT, what's working, what isn't, and where leaders should invest.

The GPT-4.1 Deprecation Forces Organizations to Change

The 2026 deprecation of OpenAI's GPT-4.1 forces a fundamental shift in enterprise AI. Learn how the transition to reasoning models impacts cost and latency, and explore viable alternatives like open-weights and AI model routers.

What Is Budget Pacing in Programmatic Advertising?

A practical guide to budget pacing in programmatic advertising — why greedy spend wrecks ROAS, how to separate forecasting from real-time control, and which algorithms (Prophet, PID, MPC, RL) actually run in production.

The LLM Specialization Showdown