Industries
Pricing
Services
Benchmarks
Cyber
Talk to sales
Start
Start
Blog
Latest
October 7, 2026
·
26 min read
Optimizing LLM Apps
Prompt engineering, retrieval, and fine-tuning: when each one pays off, and the order to try them in.
Stephen M. Walker II
Co-Founder, CEO
All
Evaluation
Fine-tuning
Engineering
Guides
Industry
26 posts
2026
Jul 14
Fine-tuning
Jul 14
Fine-Tuning Guide: When It Is Worth It and How to Do It in 2026
A decision framework and production workflow for fine-tuning LLMs, from prompting and RAG through datasets, evaluation, training, deployment, and monitoring.
Fine-tuning
Jul 14
Fine-tuning
Jul 14
Fine-Tuning OpenAI Models: What Still Works
The OpenAI models you can still fine-tune, the current API syntax and pricing, and what to decide before self-serve fine-tuning closes.
Fine-tuning
Jul 14
Fine-tuning
Jul 14
Fine-Tuning GPT-4 with OpenAI's API: A Current Guide
What remains fine-tunable in the GPT-4 family, the current API and data format, and the available alternatives.
Fine-tuning
Jul 14
Evaluation
Jul 14
How Teams Actually Agree a Prompt Got Better
A repeatable workflow for mixed teams to decide whether a new prompt version is actually better, and to keep a written record of why.
Evaluation
Jul 14
Engineering
Jul 14
The Best AI Tools for Startups in 2026: A Stack That Earns Its Cost
An AI tool stack for startups sorted by job, with what each tool sees about your company and when to skip it.
Engineering
2025
Dec 15
Evaluation
Dec 15
Comparative Analysis: Google Gemini Pro vs. OpenAI GPT-3.5
Gemini Pro beat GPT-3.5 on speed, reading comprehension, instruction following, and code, but its API design and safety blocking kept us on OpenAI.
Evaluation
Dec 8
Engineering
Dec 8
Building Your AI Team in 2025
Five team shapes, the capabilities every team needs, and a working evaluation loop, from a year of conversations with AI product teams.
Engineering
Dec 8
Engineering
Dec 8
Prompt Engineering Guide: A Comprehensive Examination of Prompt Techniques
Prompt formats for each major model family, techniques like few-shot and chain-of-thought, and how to evaluate and iterate on prompts.
Engineering
Nov 23
Industry
Nov 23
Analyzing Retool's State of AI 2023 Report
Key findings from a survey of over 1,500 tech professionals, and what they mean for teams shipping AI features.
Industry
Nov 10
Industry
Nov 10
OpenAI DevDay 2023 Reflections
The Klu team evaluates the features OpenAI launched at DevDay 2023.
Industry
Oct 19
Guides
Oct 19
Startup Guide to Azure OpenAI
How Azure OpenAI differs from the public API, and how to use its speed and startup credits.
Guides
Oct 16
Industry
Oct 16
AI Safety in 2023: analysts claim issues up 700% in 2023
What the numbers say about AI safety in 2023, the year generative models dominated headlines and sparked calls for regulation.
Industry
Oct 10
Engineering
Oct 10
Why most Vector DBs will die – Pt.01
Why Klu built its vector search on pgvector and Supabase instead of Pinecone, and why retrieval latency barely registers next to LLM generation time.
Engineering
Oct 6
Industry
Oct 6
AI in the News: Alignment, Doom, Risk, and Understanding
Common misconceptions about understanding, controlling, and aligning AI systems, broken down.
Industry
Sep 23
Guides
Sep 23
Guide: Getting started with Klu Python SDK
Build your first Klu Action with the Python SDK in five steps.
Guides
Sep 23
Guides
Sep 23
Guide: Getting started with Klu TypeScript SDK
Build your first Klu Action with the TypeScript SDK in five steps.
Guides
Sep 22
Engineering
Sep 22
Just Launched: Our expanded, global OpenAI GPT-4 deployment
Klu's Azure OpenAI GPT-4 deployment across 15 regions, the full region list, and why redundancy, load scaling, and regional privacy drove it.
Engineering
Sep 1
Evaluation
Sep 1
Everything We Know About GPT-4
A GPT-4 model card compiled from public research: about 1.8 trillion parameters, mixture-of-experts architecture, training compute, data, and known limitations.
Evaluation
Sep 1
Fine-tuning
Sep 1
OpenAI SDK: Fine-tune GPT-3.5 Turbo
Format, clean, and upload your data, then train and evaluate a GPT-3.5 Turbo fine-tune, with a Joe Rogan comedy model as the example.
Fine-tuning
Aug 28
Evaluation
Aug 28
Open Source LLMs: Exploring 5 Popular Models in August 2023
Llama 2, Vicuna, Falcon, MPT, and StableLM compared on architecture, training data, and benchmarks, plus three ways to run them on a laptop.
Evaluation
Aug 19
Industry
Aug 19
AI Collaboration: the key to breakout products
How companies pair human judgment with AI in healthcare, marketing, and manufacturing, and the ethics and reskilling work that adoption requires.
Industry
Jul 17
Evaluation
Jul 17
Best Open Source LLMs of 2025
A ranked list of open source LLMs, plus how to test them online, run them locally, fine-tune them, and serve them in production.
Evaluation
Jul 12
Evaluation
Jul 12
Evaluating 2024 Frontier Model Capabilities Pt.01
We built QUAKE to test frontier models on everyday knowledge-work tasks, and the 2024 models averaged 28% under human review.
Evaluation
Jul 8
Evaluation
Jul 8
Unleashing the Power of Multimodal AI Models: Understanding the Future of Artificial Intelligence
How GPT-4V, Gemini Vision, LLaVA 1.5, and Fuyu-8B handle text and images, with a leaderboard, integration challenges, and real applications.
Evaluation
Jul 4
Industry
Jul 4
AI Readiness: 7 Key Areas to Evaluate for Successful AI Implementation
Seven areas to assess before adopting AI: strategy, culture, data, infrastructure, ethics, change management, and how you measure success.
Industry