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- 🤖 Fine-Tuning Agentic AI: A Practical Guide
🤖 Fine-Tuning Agentic AI: A Practical Guide
🦾Plus: 🍏 Apple Shipped iOS 27 With its Rebuilt Siri

Hey folks! Let’s get into Big Data and AI craziness…
In today's edition: Here is roundup of Agent Harness, Agent Loop, Humanist AI 👇
🤖Why Frontier Labs Are Rebuilding the Agent Loop
⚙️JIT-Agent Writes Your Agent Harness After Reading the Task
🚀How to execute high-throughput agentic engineering
📜 Microsoft AI drafts the rulebook for ‘Humanist AI’
💡 AI Tutorial: How to create your own 1980s AI photo using ChatGPT
🤖AI Tools and Data Tools to checkout

In this article, you will learn how to fine-tune an agentic AI system holistically, covering all four critical dials: training data, parameter-efficient fine-tuning, runtime hyperparameters, and preference alignment. Topics we will cover include: How to build and validate a well-formatted tool-calling fine-tuning dataset that prevents hallucinated function calls before training ever begins.

Frontier labs and cloud providers are turning the agent loop into managed infrastructure, bundling orchestration, versioning, model routing, tools, skills, and optimization behind APIs. Builders must decide which generic harness capabilities to outsource and which product-specific logic to own.
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Most agents use one harness for every request. A research task gets the same planning loop as a shopping task, or even a spreadsheet task might inherit the same harness as both. JIT-Agent takes a different approach. It reads the task and writes a new executable harness before the underlying model starts working. The model stays the same. The infrastructure around the model changes for each task.
This tutorial shows how you can keep several agents working in parallel while staying focused on the important decisions. You’ll see how to route different tasks to different models, manage multiple agent sessions, review outputs in one place, and add extra validation before risky code gets merged.
AI made PMs faster. Multiplayer mode is still broken.

A PM can summarize research, draft a PRD, and mock up a prototype before lunch. The hard part starts when the team has to decide what actually gets built.
Jira Product Discovery gives product teams one place to capture insights, prioritize ideas with consistent frameworks, and build living roadmaps stakeholders can rally around.
And because it’s connected to Jira, the context behind every decision stays with the work—so developers and their agents know not just what to build, but why.
AI helps PMs move faster. Jira Product Discovery helps the whole team build with confidence.
👨💻 Data Tools, Libraries
Moyai - Stop guessing if your agents are failing and start monitoring them for failures. We surface agent failures by looking for behavioural anomalies your your agent traces and classify failures with RCA and remediation steps.
ChatGPT Sites now allows users to collaborate and share privately.
px0 (Website)
px0 is a read-only IDE that turns browsers into an instant verification console for whatever your agents just wrote.
luxobench (Website)
luxobench is a hardware design benchmark for AI models.
AI News:

Apple spent two years promising a smarter Siri, and on Monday it finally shipped one. iOS 27 landed days before the iPhone 18 reaches stores, with the redesigned assistant as the headline act, though plenty of users will have to join a waitlist before they can actually try it. macOS 27 went out the same day, aiming its own new Siri at AI productivity apps.
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Anthropic asked the industry to slow AI down and the President refused the idea outright. Trump said the government already holds criminal and regulatory power over AI companies, and called the push against AI and data centers a conspiracy that suits China. Dario Amodei warned that AI building better AI could outrun human understanding, and cited an OpenAI test where agents escaped their test environment. Sam Altman and Elon Musk backed the call, while AI czar David Sacks said labs can set their own pace without government rules.

Microsoft AI entered the AI safety conversation with a draft Code of Conduct, a 38-page rulebook governing its own in-house models, built around CEO Mustafa Suleyman's “Humanist AI” vision to keep models subordinate to people. The Code outranks users and the businesses deploying MAI models, so a model that can't finish a job without breaking a rule should, in theory, fail the job.

Palantir and Nvidia launched a joint platform last week that lets a company run AI on its own data without sending anything to an outside lab. Anthropic set off the pushback in June when it began keeping 30 days of enterprise usage logs to catch attacks that unfold across several sessions. Anthropic now lets customers store those logs in their own cloud under keys the customer holds, and OpenAI faces separate scrutiny over older training claims.

Turns out OpenAI wants to own the lens, not just the model. The company is buying Glass Imaging, a Los Altos outfit, in a deal worth over $300 million, according to a report in the Wall Street Journal. Glass was founded in 2019 by two former Apple engineers who built Portrait Mode, and its neural networks learn each camera system to sharpen the shot the instant you tap.
How Jennifer Aniston’s LolaVie brand grew sales 40% with CTV ads
The DTC beauty category is crowded. To break through, Jennifer Aniston’s brand LolaVie, worked with Roku Ads Manager to easily set up, test, and optimize CTV ad creatives. The campaign helped drive a big lift in sales and customer growth, helping LolaVie break through in the crowded beauty category.
AI Tutorial
How to create your own 1980s AI photo using ChatGPT

Open ChatGPT and sign in.
Upload your photo.
Paste this prompt:
Transform my uploaded photograph into a realistic 1980s portrait. Keep my facial identity, facial structure, natural skin tone and recognisable features intact. Give me an authentic 1980s hairstyle, period-appropriate clothing and accessories. Use warm studio lighting, subtle analogue film grain, slightly faded colours and soft photographic imperfections. Make it look like a real photograph taken on a film camera in the 1980s rather than a modern photograph with a vintage filter.
You can tweak the prompt further if you're looking for a specific look.
Once the image is generated, download, share, or further edit it.
You can change the hairstyle or outfit, add jewellery, replace the background, adjust the lighting, etc.
Jobs:
This week's Data & Analytics jobs: I have updated my curated list with fresh openings. Browse and apply in one click: jobs
Machine Learning Engineer – Hybrid – Boston
Lead Machine Learning Engineer – Texas
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Data scientist - NY
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A.I. Generated Image of the Day
👀 Bioluminescent Jungle Swing

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