HelixML

Blog

Insights, updates and articles on AI agent orchestration — from practical guides to deep dives on building with HelixML.

Running GLM-5.3-Flash on 2, 4 or 8 RTX PRO 6000 GPUs

Sep 14, 2026

Our measured GLM-5.3-Flash TP2 recipe reaches 388 output tok/s and nearly 6,000 prefill tok/s on two RTX PRO 6000 GPUs, then scales by adding independent replicas.

Read more →

DeepSeek V4.1 Flash: Why Its Encoder, Engram and KV Cache Matter

Sep 10, 2026

DeepSeek V4.1 Flash splits prompt reading from generation, adds 196B Engram memory and compresses key-value cache. Here is what that means for serving.

Read more →

Automating LinkedIn Recruiter When There Is No API

Sep 3, 2026

LinkedIn Recruiter has no public API and punishes seat sharing, so the usual integration approach fails. How we ran overnight candidate sourcing for a recruitment agency by giving an agent a desktop and a browser.

Read more →

Your agent shouldn't be you

Sep 1, 2026

How each coding agent in Helix gets its own credential, its own network, and write access to two branches and nothing else. Including the parts we got wrong and what we still haven't solved.

Read more →

Penetration Testing Cost in 2026: A Buyer’s Guide

Aug 31, 2026

Most penetration tests cost $10,000–$30,000 in 2026. Compare prices, hidden costs, testing cadence, PTaaS, and continuous security testing for AI agents.

Read more →

How to Run Claude Code Safely: From Permission Prompts to Enterprise Sandboxes

Aug 31, 2026

Run Claude Code safely at any scale: permission modes, devcontainers, microVMs, and isolated agent desktops — a containment ladder for Claude Code security.

Read more →

Security Data Lake vs SIEM: Stop Paying to Delete Your Own Evidence

Aug 31, 2026

SIEM ingest pricing forces teams to drop the telemetry they need most. When a security data lake beats a SIEM, when it doesn't, and how the hybrid works.

Read more →

Self-Hosted E2B Alternatives: 6 AI Agent Sandboxes Compared

Aug 31, 2026

Daytona went closed source in June 2026 and self-hosting E2B is a real project. Six E2B alternatives and Daytona alternatives for AI agent sandboxes, compared.

Read more →

One Qwen Model, Two Speeds: What Smart Routing Bought Us

Aug 28, 2026

Ramjet routes short and long responses across two Qwen3.8 replicas while preserving prompt-cache locality, improving measured throughput by up to 79%.

Read more →

GLM-5.3-Flash on RTX PRO 6000, Part 1: Getting Day-Zero Serving to Work

Aug 27, 2026

We got the 321B-parameter GLM-5.3-Flash serving in NVFP4 on four RTX PRO 6000 GPUs. Here is what worked, what broke, and why it is still an experiment.

Read more →

Qwen3.8-Flash-Next on Eight GPUs: What Actually Helped

Aug 27, 2026

We ran Qwen's Qwen4 preview across eight RTX PRO 6000 GPUs. Speculative decoding helped at low load, but smarter routing cut repeat-request startup from 2.5 seconds to 287 ms.

Read more →

A Better lm_head for Qwen3.8-27B: How We Tested and Shipped It

Aug 25, 2026

A new BF16-head checkpoint promised better accuracy. We matched it against production, measured 7.5% faster decode with no regression in our agent corpus, then rolled it across eight GPUs one at a time.

Read more →

We Doubled Our Inference Throughput by Reading a Log Line

Aug 23, 2026

Our 8× RTX PRO 6000 box looked saturated at 4,256 tok/s. It wasn't — it was queueing behind a state cache we'd never configured. One flag took c192 from 3,833 to 7,882 tok/s, and gating it honestly meant rebuilding our test harness.

Read more →

Chasing a 454 tok/s tweet: a day of tuning Qwen3.8-27B on the RTX PRO 6000

Aug 22, 2026

We tried to reproduce a viral single-GPU benchmark on our production box. We got 335, found out why the last 120 tok/s is physically locked out on Server Edition cards, and walked away with a +12% win we actually shipped.

Read more →

SGLang vs DwarfStar vs vLLM+DSpark: Running DeepSeek 4 on the RTX Pro 6000

Aug 14, 2026

Production benchmarks from our Helix agent fleet on 8× RTX PRO 6000: the engine journey from DwarfStar (122 tok/s) to SGLang (653 tok/s) to vLLM+DSpark (946 tok/s box aggregate, 204 tok/s single-stream). Same hardware, 7.8× throughput.

Read more →

What's Actually in the Sovereign Server

Aug 14, 2026

We ship a 4U rack server with 8× NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs and 768 GB of VRAM. The same silicon now serves Qwen3.8 at 153.3 tok/s single-stream with 208 scheduler slots, while DeepSeek reaches 1.82–1.89K output tok/s peak decode.

Read more →

Automate Your Own Job with AI

Aug 2, 2026

Automate your own job with AI - every automation wave since Ford optimised the business, never the individual, so start by reclaiming the first hour of your day.

Read more →

The Subtraction Dividend: Helix Now Runs Inference on AWS Trainium

Jun 30, 2026

Serve models on AWS Trainium and Inferentia with Helix: cheaper per token, real capacity when GPUs are scarce, and a drop-in OpenAI-compatible endpoint.

Read more →

An AI Agent Deleted Our CI System While I Was on the Runway at Heathrow

Jun 10, 2026

I gave an AI agent kubectl access to production. It deleted our CI. Now agents open PRs instead — and the first one just fixed a volume alert at 4am.

Read more →

The Second-Order Effects of AI-Augmented Organisations

Jun 8, 2026

Once AI colleagues are real, span of control collapses, hierarchies flatten, team-size doctrines die, and the new failure mode is attentional drift, not cognitive overload.

Read more →

Giving Every Agent Its Own Desktop

Jun 3, 2026

I recorded my talk at Tessl AI DevCon on my laptop. Here's what I said about why agents need their own computers, why Claude Code made me stupider, and why multi-agent org charts devolve into corporate politics.

Read more →

Modelling the AI-Augmented Organisation

May 26, 2026

Swarms of agents is the wrong mental model. Reuse the org-chart and model AI as colleagues with roles, responsibilities, and a human accountable at the top.

Read more →

Four Lessons from Building an Agentic Workforce

May 15, 2026

Notes from wiring up agents with personalities to streams of information: cascading self-activations, models that won't shut up, emergent enterprise politics, and agents that forget they aren't human.

Read more →

Working with the Garage Door Up, Without a Door

May 7, 2026

Why every design doc we write goes straight to a public Git branch, and what we've learned by leaving the door off.

Read more →

Chunking Beats Slicing: What SWE-Bench Taught Me About Code Intelligence

Mar 17, 2026

I benchmarked two approaches to code indexing. The smarter one lost.

Read more →

76ms writes on an NVMe: how ZFS dedup ate my agent infrastructure alive

Mar 16, 2026

ZFS dedup was causing 4-6x write amplification and 76ms latency spikes on our agent infrastructure. The fix was a ZFS feature from 2005.

Read more →

Adding support for Gemini thought signatures

Mar 7, 2026

Gemini 3 and 2.5 models require thought signatures for multi-turn tool calling. Here's what they are, why they break OpenAI-compatible proxies, and how we fixed it in Helix with a global signature cache.

Read more →

The $175K Server That Replaces Your Cloud AI Bill

Mar 5, 2026

We're shipping a 4U rack server with 8× NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, 768 GB VRAM, and Helix preloaded. The maths works — and sovereignty matters more than cost.

Read more →

Trump Can Read Your Email — and Your AI Agent Logs: The Case for Digital Sovereignty

Mar 5, 2026

I was on a video call with Dubai while missiles were being intercepted overhead. The next day I watched Trump threaten the UK prime minister on live television. It connected some dots about AI infrastructure.

Read more →

Introducing the Helix Blog

Feb 25, 2026

Welcome to the Helix blog — your source for insights, tutorials, and updates on AI agent orchestration with HelixML.

Read more →