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AI & Automation Chronicle

Research discussions

In-depth breakdowns of AI, data science, and automation research - written for practitioners, with live weekly Zoom discussions. From Satish K C's portfolio.

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Each article ships with a live session - deeper Q&A, practitioner takeaways, and how the ideas connect to production agent systems.

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July 2026

June 2026

AgentsOptimizationLLMs

Week 20 · June 2026

Autodata: When an AI Agent Writes Your Training Data

Meta FAIR's Autodata uses a four-agent loop - Challenger, Weak Solver, Strong Solver, Verifier - to generate synthetic training data at the right difficulty level. A 4B model trained on 2,800 agentic examples outperforms the 397B baseline on legal reasoning without any RL fine-tuning.

Research8 min read
AgentsAutomationn8n

Article 16 · June 2026

Enterprise Field Services: AI-Powered Sales, Ops and Financial Reconciliation Automation

12 production automations across Calendly, Monday.com, PaintScout, CompanyCam, Brevo, RabbitMQ, and Gemini AI. 80% admin overhead reduction. A full teardown of how to wire an end-to-end field services stack - from lead capture through 5-day follow-up sequences to AI receipt reconciliation with race condition prevention.

Practice9 min read
AgentsRAGLLMs

Week 19 · June 2026

AtomMem: Building Long-Term Agent Memory from Atomic Facts

AtomMem replaces summary-based memory with verified atomic facts organized into event hierarchies, temporal user profiles with version history, and an associative graph for multi-hop retrieval. It achieves 42.50 Multi-Hop F1 and 62.78 Temporal F1 on LoCoMo - best in class on both - while using 61% fewer tokens than MEM0.

Research8 min read
AgentsOptimizationLLMs

Week 18 · June 2026

SkillOpt: Teaching Agents to Improve Their Own Instructions

SkillOpt treats agent skills as trainable external documents, using a separate optimizer model to iteratively refine them via bounded add/delete/replace edits. On GPT-5.5, it delivers +23.5 points on average across six benchmarks - and optimized skills transfer across models and harnesses without retraining.

Research8 min read
AgentsLLMsEfficiency

Article 15 · June 2026

Claude Fable 5 Is Live: What Changes for Practitioners Building on Claude

Stripe compressed months of engineering work into days. File-based memory benefits are 3x larger than Opus 4.8. Vision-only harnesses now sufficient for complex tasks. Here is what the Fable 5 capability jump, new three-classifier safeguard architecture, and halved pricing mean for automation practitioners.

Practice8 min read
Deep LearningTransformersLLMs

Week 17

Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference

Standard transformers and SSM-attention hybrids (Samba, HYMBA) both fail on long-horizon math reasoning tasks. A sleep-like mechanism distills KV cache context into persistent fast weights via N offline recurrent passes - preserving inference latency while improving deep reasoning performance with each additional pass.

Research8 min read
AgentsLLMsOptimization

Week 16

Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents

Aggregate pass@1 drops 24 percentage points (76.3% to 52.1%) as task duration grows across 10 models and 23,392 episodes. Memory scaffolds never helped any model and hurt 6 of 10 - the standard long-horizon intervention is empirically wrong.

Research8 min read

May 2026

AgentsTransformersLLMs

Week 15

Hermes: Chain-of-LLM Agents for Autonomous Network Modeling

A chain of specialized LLM agents using structured YAML blueprints achieves 82.5% success rate for autonomous network modeling - a 3.3x improvement over chain-of-thought on the same GPT-4o model. The harness thesis gets its domain-specific proof.

Research8 min read
AgentsOptimizationLLMs

Week 14

From Model Scaling to System Scaling: The Harness Is the New Leverage

Shangding Gu argues that harness engineering - tools, memory, context management, orchestration - now delivers superior performance gains to raw model scaling for agentic tasks, confirmed by SWE-bench, AgentBench, WebArena, and TerminalBench results.

Research8 min read
AgentsLLMsRAG

Article 14 · May 2026

Two Anthropic Playbooks for Production Agents: Context Engineering and Long-Running Harnesses

Anthropic published two engineering posts that form a complete production playbook: context engineering to manage the token ecosystem across turns, and agent harnesses to prevent the four failure modes that collapse long-running agents - from one-shotting tasks to declaring premature victory.

Practice9 min read
AI SafetyAgentsSecurity

Article 13 · May 2026

AI Agent Traps: The New Attack Surface for Autonomous Agents

Google DeepMind's first systematic taxonomy of adversarial content targeting AI agents - six attack categories spanning perception, reasoning, memory, action, multi-agent dynamics, and the human overseer. Content injection achieves 86% agent commandeer rate; data exfiltration succeeds in 80%+ of tested agents.

Research10 min read
LLMsAgentsEfficiency

Article 12 · May 2026

Gemini 3.5 Flash: Budget Model, Frontier Agentic Performance

Google DeepMind's Flash-tier model beats Claude Opus 4.7 and GPT-5.5 on MCP Atlas (83.6%), Finance Agent v2 (57.9%), and MMMU-Pro (83.6%) while offering controllable thinking levels and 1M token context at budget pricing.

Practice8 min read
Deep LearningEfficiencyLLMs

Week 12 · May 2026

IceCache: Cutting LLM Memory Costs Without Cutting Quality

KV cache memory scales linearly with sequence length - making long-context inference expensive or impossible on constrained hardware. IceCache clusters tokens semantically using a DCI-tree index, retaining 99% of full-cache accuracy at 256 tokens and outperforming PQCache at 4x the budget.

Research8 min read
AgentsRAGLLMs

Article 11 · May 2026

How Databricks Built a Data Agent That Actually Works

Generic coding agents fail on enterprise data tasks - wrong tables selected, no way to verify SQL correctness, one model doing everything. Databricks rebuilt Genie with specialized knowledge search (+40% table discovery), parallel SQL sampling, and multi-LLM routing. Result: accuracy from 32% to 90%+.

Practice8 min read
AgentsLLMsAutomation

Article 10 · May 2026

Agents-as-a-Service vs Conventional Software: A New Delivery Model

The software industry is splitting: those selling seats vs those selling outcomes. AaaS deploys autonomous AI agents that execute entire workflows end-to-end. Pay per task completed, not per seat occupied. 80% margins at scale, days to deploy, and vertical specialization beats horizontal platforms.

Practice8 min read
LLMsAgentsRAG

Article 09 · May 2026

Prompt Engineering is Dead. Long Live Context Engineering.

The AI industry declared the shift: building production systems is no longer about crafting the perfect prompt. Context engineering - assembling RAG results, tools, memory, and state into the context window at runtime - is the discipline that separates demos from production agents. 3x tool selection improvement, 15x token tradeoffs, and four failure modes to avoid.

Practice8 min read
Deep LearningEfficiencyNLP

Week 11 · May 2026

Physics-Informed Machine Learning: When Biomedical Models Need Both Data and Physical Laws

Three PIML frameworks - PINNs, Neural ODEs, Neural Operators - are reshaping biomedical modeling by embedding governing equations into ML loss functions. 10-100x less training data needed, 1000x speedup over FEM for parametric PDEs, and physically-guaranteed plausible predictions. Review from Brown and Yale in Annual Review of Biomedical Engineering.

Research8 min read
Healthcare AIAgentsLLMs

Article 08 · May 2026

AMIE: Google's Diagnostic AI Just Passed Its First Real-World Clinical Test

Google deployed its AMIE diagnostic agent in a real primary care clinic for the first time - 100 patients, zero safety interventions, 90% top-7 diagnostic accuracy. Clinicians say the AI pre-visit summaries transformed their appointments from data gathering to collaborative decision-making.

Practice8 min read
Deep LearningLLMsAgents

Week 10 · May 2026

OCR-Memory: Why Text-Based Agent Memory Loses Evidence - and How Visual Encoding Fixes It

Text memory either burns tokens or loses detail. OCR-Memory from HKU and UNT renders agent trajectories as images, retrieves verbatim evidence through visual anchors with 100% faithfulness, and cuts reasoning tokens by 6.7x - hitting 58.1% on AppWorld and 53.8% Element Accuracy on Mind2Web. Accepted at ACL 2026.

Research8 min read

April 2026

Deep LearningLLMsAgents

Week 09 · April 2026

StructMem: Why Flat Memory Breaks on Long Conversations - and How Hierarchical Design Fixes It

Flat memory plateaus at 60 entries. Graph memory costs 18x more tokens. StructMem from Zhejiang University and Ant Group finds the middle ground - hierarchical event binding with cross-event consolidation hits 76.82% on LoCoMo with only 1,056 API calls.

Research8 min read
Deep LearningLLMsRLHF

Week 08 · April 2026

GDPO: Why GRPO Breaks Under Multiple Rewards - and How to Fix It

NVIDIA researchers show that GRPO's reward normalization collapses distinct advantage signals when multiple rewards are used together, causing training instability. GDPO decouples normalization per reward, boosting AIME accuracy from 23.1% to 29.4% and eliminating training collapse.

Research7 min read
Deep LearningGenerative ModelsComputer Vision

Week 07 · April 2026

Generative Modeling via Drifting - One Step Is All You Need

MIT and Harvard researchers introduce Drifting Models - a new generative paradigm that achieves FID 1.54 on ImageNet 256x256 in a single forward pass, matching 500-step diffusion models. No distillation, no adversarial loss.

Research7 min read
QuantizationEfficiencyLLMs

Article 07 · April 2026

TurboQuant: 6x Memory, 8x Speed, Zero Accuracy Loss - Google Redefined KV Cache Compression

Google Research's TurboQuant compresses the KV cache of large language models to 3-bit precision with no training and no accuracy loss. Three coordinated algorithms deliver 6x memory reduction and 8x attention speedup on H100 GPUs - changing the economics of long-context inference.

Practice8 min read
LLMsSecurityPrivacy

Week 06 · April 2026

Large-scale Online Deanonymization with LLMs

Researchers from MATS, ETH Zurich, and Anthropic show that an LLM pipeline achieves 68% recall at 90% precision re-identifying pseudonymous users - compared to near 0% for all prior methods. Practical obscurity no longer holds.

Research16 min read
LLMsOpen SourceOptimization

Article 06 · April 2026

Gemma 4 Goes Apache 2.0 - What the License Shift Really Means for Builders

Google's Gemma 4 is the first in the family to carry an OSI-approved Apache 2.0 license. Covering models from edge-deployable sub-1B up to 31B parameters, it removes the legal barrier that kept enterprises from fully committing to Gemma in production.

Practice9 min read
AgentsAutomationVision AI

Article 05 · April 2026

IBM Granite 4.0 3B Vision: The Compact VLM Built for Document Extraction

IBM Research's 4B-parameter VLM turns charts, tables, and invoices into structured data with a single tag-driven API call. 85.5% KVP accuracy zero-shot, Apache 2.0, and vLLM-native.

Practice11 min read

March 2026

Deep LearningTransformersNLP

Week 05 · March 2026

DeepSeek-OCR 2: Visual Causal Flow

DeepSeek AI replaces CLIP ViT with Qwen2-0.5B as the vision encoder and introduces causal flow queries that attend to document regions in semantic order. Achieves 91.09% on OmniDocBench v1.5 and outperforms Gemini-3 Pro at the same 1,120-token budget.

Research14 min read
Deep LearningEfficiencyOptimization

Week 04 · March 2026

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Gu and Dao's ICLR 2024 paper makes SSM parameters input-dependent, enabling content-aware sequence modeling at O(L) complexity. Mamba-1.4B matches Pythia-6.9B on language modeling perplexity while delivering 5x higher inference throughput than Transformers at sequence length 2K.

Research15 min read
AgentsLLMsAutomation

Article 04 · March 2026

Claude vs OpenAI for Automation - A Practitioner's Decision Framework

Both APIs can power your automation pipeline. The decision comes down to context window, prompt caching economics, instruction fidelity, and ecosystem fit - not brand preference.

Practice12 min read
Deep LearningCausal AIOptimization

Week 03 · March 2026

CausalMMM: Learning Causal Structure for Marketing Mix Modeling

WSDM 2024 paper from Chinese Academy of Sciences that automatically discovers shop-specific causal graphs across advertising channels using variational inference, beating InGRA by 5.7-7.1% AUROC and cutting GMV prediction MSE by 13% at M=7 steps.

Research14 min read
AgentsAutomationLLMs

Article 03 · March 2026

The Agentic Development Cycle - How AI Agents Actually Build Software

AI agents do not just autocomplete code - they run a full observe-plan-act-reflect loop. Here is what structurally changes when the implementation loop is no longer yours to run.

Practice11 min read
AutomationEdge ComputingBots

Article 02 · March 2026

$17 and Always-On: Running PicoClaw on Cheap Hardware

Under 10MB RAM, 1-second boot, and a $17 board. How PicoClaw became my always-on automation engine - and why the hybrid PicoClaw + OpenClaw setup is the real sweet spot.

Practice9 min read
LLMsQuantizationEfficiency

Week 02 · March 2026

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Microsoft Research proves that ternary-weight LLMs ({-1, 0, +1}) can match full-precision models while delivering 4x lower latency, 3.5x less memory, and 71x energy savings.

Research13 min read
AgentsAutomation

Article 01 · March 2026

Is Monday.com the New Excel - but with AI that actually thinks?

Monday.com is quietly evolving from a project tracker into an AI-powered Work OS. Here's what's really happening under the hood.

Practice10 min read
Deep Learning

Week 01 · March 2026

Attention Is All You Need - Revisited

A deep dive into the original Transformer paper and why it still shapes every modern LLM architecture today.

Research8 min read