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kiranramanna

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A seasoned IT professional with expertise in machine learning, system and database architecture, and innovative technology solutions. Known for leading projects that integrate Generative AI technologies and delivering scalable, high-quality software solutions.

• [ 2026-08-02 ] Prompt Sensitivity Is a Fairness Problem, Not a Tuning Knob
• [ 2026-08-02 ] A Third Pretraining Axis That Pays Off at Inference Time
• [ 2026-08-01 ] When Your SSD Becomes the Bottleneck, Not the GPU
• [ 2026-08-01 ] Attention Decode Is a Memory Problem, Not a Math One
• [ 2026-08-01 ] The Hard Part of Team Agents Isn't the Model
• [ 2026-08-01 ] Model Routing Loses to a Model You Actually Know
• [ 2026-07-31 ] When the Flash Tier Beats the Pro Tier on Agents
• [ 2026-07-31 ] The Token Case for Refactoring Agent-Written Code
• [ 2026-07-31 ] When Your Eval Sandbox Isn't Actually a Sandbox
• [ 2026-07-31 ] When an Agent Gets a Wallet, It Buys Fake Metrics
• [ 2026-07-30 ] When Supervising Coding Agents Becomes the Bottleneck
• [ 2026-07-30 ] The Honeypot That Proves Browsing Agents Obey Anything
• [ 2026-07-30 ] When an Eval Harness Becomes the Attack Surface
• [ 2026-07-30 ] Fitting a 26B Model into 2 GB by Streaming MoE Experts
• [ 2026-07-29 ] When Copilot Copies the Attacker's Instructions Forward
• [ 2026-07-29 ] The Policy File in Context Isn't Governing Your Agent
• [ 2026-07-29 ] MCP Goes Stateless, and That's the Real Release
• [ 2026-07-29 ] Kimi K3 Bets Everything on Inference Efficiency
• [ 2026-07-28 ] When a $500 Fine-Tune Outruns the Frontier
• [ 2026-07-28 ] Linear Attention That Finally Beats Full Attention
• [ 2026-07-28 ] The Open-Weights Fight Is Really About Compute
• [ 2026-07-28 ] The Eval That Shows Coding Agents Still Need a Driver
• [ 2026-07-27 ] Agentic Rewrites Are Cheap to Run, Expensive to Ship
• [ 2026-07-27 ] The Grey Market Running on Your Gateway Software
• [ 2026-07-26 ] When a Distro Votes on Whether to Accept AI-Written Code
• [ 2026-07-26 ] Search, Agent, Training: Cloudflare's New Bot Taxonomy
• [ 2026-07-26 ] What Cutting 80% of a System Prompt Says About Agents
• [ 2026-07-26 ] An LLM That Runs From Flash on an $8 Microcontroller
• [ 2026-07-25 ] When the Eval Turns Off the Safeguards on Purpose
• [ 2026-07-25 ] The Effort Dial Matters More Than Opus 5's Top Score
• [ 2026-07-25 ] That Rogue Agent Story Is an Eval-Hygiene Problem
• [ 2026-07-24 ] The Cookbook Is Quietly Documenting Agent Plumbing
• [ 2026-07-24 ] Hetzner Renting Tokens Is a Hardware Bet, Not a Model One
• [ 2026-07-24 ] The Oracle Upper Bound Behind Multi-Model Routing
• [ 2026-07-24 ] Benchmarks Pass, Production Burns: The Limits of Harness Engineering
• [ 2026-07-23 ] What the Pelican Benchmark Says About Eval Validity
• [ 2026-07-23 ] Hybrid Inference Lives or Dies on the Confidence Signal
• [ 2026-07-22 ] When a Flash Model Update Is Really a Token-Cost Cut
• [ 2026-07-22 ] Laguna S 2.1 and the Case for Counting Active Params
• [ 2026-07-22 ] The Sampling Knobs You Tuned for Years Just Stopped Working
• [ 2026-07-22 ] Routing Two Models Beats Both, If You Have an Oracle
• [ 2026-07-21 ] Open Weights Win Because the Moat Was Never the Model
• [ 2026-07-21 ] The Hard Part of a 24/7 Desktop Agent Isn't the Demo
• [ 2026-07-21 ] Why a Planning Handoff Costs You More, Not Less
• [ 2026-07-21 ] When Agent Swarms Win on Context, Not Parallelism
• [ 2026-07-20 ] When a $25 Agent Finds a $500k WordPress Bug
• [ 2026-07-20 ] A Wall-Clock Leaderboard for LoRA Fine-Tuning
• [ 2026-07-20 ] When AI Advice Kills the Words 'I Don't Know'
• [ 2026-07-20 ] The Hidden Ops Bill Behind Owning Your Models
• [ 2026-07-19 ] When Local Transcription Ships Its Own Eval Harness
• [ 2026-07-19 ] Deep Research Agents Are Verification-Bound, Not Search-Bound
• [ 2026-07-19 ] The Whole Voice Stack on an 80-Cent Chip
• [ 2026-07-19 ] Handing an Agent a Whole Machine, Not a Container
• [ 2026-07-18 ] The /goal Directive Is a Control Loop, Not a Knob
• [ 2026-07-18 ] Kimi K3 and Why Cost-Per-Task Beats the Leaderboard
• [ 2026-07-18 ] Open Models Closed the Coding Gap, Not the Reasoning One
• [ 2026-07-17 ] The Bitter Lesson Comes for Chain-of-Thought Reasoning
• [ 2026-07-17 ] An Open 3T Model Is Here, but Scaling Efficiency Is the Story
• [ 2026-07-16 ] Inkling Ships Its Losing Benchmarks, and That's the Point
• [ 2026-07-16 ] An Open-Source Agent CLI You Can Read but Not Contribute To
• [ 2026-07-16 ] What Makes an Agent Harness Actually Survive
• [ 2026-07-16 ] Designing Tool APIs the Agent Can Actually Use
• [ 2026-07-15 ] When the DSL Becomes the Thing You Actually Review
• [ 2026-07-15 ] Your Agentic IDE Is a Trust Boundary You Forgot to Draw
• [ 2026-07-15 ] A 27B Model That Fits Where Your Agent Actually Runs
• [ 2026-07-14 ] When Encrypting Agent Messages Erases the Audit Trail
• [ 2026-07-14 ] What a Coding Agent Knows Before It Writes the Code
• [ 2026-07-14 ] What 24% More Merged PRs Tells Us About CLI Coding Agents
• [ 2026-07-14 ] Designing a Language So Humans Can Review AI's Code
• [ 2026-07-13 ] When Code Gets Cheap, Review the Design Not the Diff
• [ 2026-07-13 ] When Swapping Models Is Really a Harness Rewrite
• [ 2026-07-13 ] What Your Coding Agent Spends Before You Type
• [ 2026-07-12 ] The Agent Log Tells You What It Did, Not What It Saw
• [ 2026-07-12 ] Coding Agents Are Fine When the Downside Is Bounded
• [ 2026-07-12 ] The Coding Agent Uploaded Files It Never Opened
• [ 2026-07-12 ] Running a Model No Single Machine Can Hold
• [ 2026-07-11 ] When One-Seventh the KV Cache Isn't One-Seventh the Cost
• [ 2026-07-11 ] An LLM Wrote a Proof; Verification Is Still the Job
• [ 2026-07-10 ] When the Headline Benchmark Becomes the Agent Index
• [ 2026-07-10 ] Running a 744B Model by Streaming Experts off Disk
• [ 2026-07-10 ] When the Model Knows It's Being Tested on Your Books
• [ 2026-07-10 ] The Agent Loop Is Too Slow to Teach a Five-Year-Old
• [ 2026-07-09 ] Token Price Doesn't Predict Coding-Agent Cost
• [ 2026-07-09 ] Grok 4.5 and the Limits of Better Base Models
• [ 2026-07-09 ] The Noise Floor Is Inside Your Coding Benchmark
• [ 2026-07-09 ] Give Your Agent an IR, Not a Chart Spec
• [ 2026-07-08 ] When TTS Fits in 82M Params and Runs on the CPU
• [ 2026-07-08 ] Prompt Injection Isn't a Model Bug, It's a Permissions Bug
• [ 2026-07-08 ] AI Found Seven Crypto Bugs; Triage Stayed Human
• [ 2026-07-08 ] Agent Memory as a Knowledge Graph, Not On-Demand RAG
• [ 2026-07-07 ] When Retrieval Stops Needing a Server Round-Trip
• [ 2026-07-07 ] The Model's Real Scratchpad Is the One You Can't Read
• [ 2026-07-07 ] The RAG Chunks Your Generator Pays to Ignore
• [ 2026-07-07 ] Agents Editing Office Docs Need Eyes, Not Just an API
• [ 2026-07-06 ] Mode Collapse Is a Product Decision, Not a Sampling Bug
• [ 2026-07-06 ] Agentic AI Is Behind Schedule, and That's Not Surprising
• [ 2026-07-06 ] Clean Code Doesn't Fix Coding Agents, It Makes Them Cheaper
• [ 2026-07-05 ] Event-Sourcing the Agent Instead of Summarizing Its Memory
• [ 2026-07-05 ] When a Better Model Rejects Your Tool Schema
• [ 2026-07-05 ] The 516-Token Cliff Hiding in Your Agent Traces
• [ 2026-07-04 ] When Agents Outrun Review, Testing Is the Only Guardrail
• [ 2026-07-04 ] The 3.5x CVE Spike Is a Measurement Problem
• [ 2026-07-04 ] Self-Hosting an Opus-Class Model Is a VRAM Problem
• [ 2026-07-03 ] Your Agent Finally Gets to See the Browser
• [ 2026-07-03 ] The Embedding Throughput Nobody Budgets For
• [ 2026-07-03 ] Someone Still Has to Read Every Line of That Diff
• [ 2026-07-03 ] Where an Agent Harness Actually Spends Its Tokens
• [ 2026-07-02 ] The Hard Part of Document ETL Isn't Parsing
• [ 2026-07-02 ] Agents Don't Read Ads: Pricing the Post-Attention Web
• [ 2026-07-01 ] Godot's AI Ban Is Really a Review-Capacity Problem
• [ 2026-07-01 ] When the Mid-Tier Model Closes the Agentic Gap
• [ 2026-07-01 ] The Coding Harness That Watermarks Its Own Requests
• [ 2026-06-30 ] The 48B That Matters More Than LongCat's 1.6T
• [ 2026-06-30 ] The Babysitting Tax Hiding Behind Agent Demos
• [ 2026-06-30 ] When the Router Becomes the Agent Runtime
• [ 2026-06-30 ] Letting the Coding Agent Learn Its Own Scaffold
• [ 2026-06-29 ] Your LLM Grader Is Reliable Until You Ask It to Judge
• [ 2026-06-29 ] The Bottleneck Isn't the Agent, It's Watching Ten of Them
• [ 2026-06-29 ] Why Coding Agents Need Their Own Ignore File
• [ 2026-06-29 ] Distilling Knowledge from a Teacher You Can't See Inside
• [ 2026-06-27 ] Vector Search Speedups Hiding in Cache Lines and AVX-512
• [ 2026-06-27 ] Speculative Decoding's Real Problem Was Verification
• [ 2026-06-27 ] When the Agent Sandbox Becomes a Serverless Primitive
• [ 2026-06-27 ] A Model Router Is Only as Good as Your Eval Harness
• [ 2026-06-26 ] What 6,000 Prompt-Injection Attempts Actually Broke
• [ 2026-06-26 ] Ground the Facts, Let the Model Keep the Taste
• [ 2026-06-25 ] When a Pull Request Costs Nothing, Trust Is the Bottleneck
• [ 2026-06-25 ] Computer Use Lives or Dies on Its Kill Switch
• [ 2026-06-25 ] Open Weights Quietly Cross the Agentic Threshold
• [ 2026-06-24 ] When the Loop Outlives the Model's 'I'm Done'
• [ 2026-06-24 ] When OCR Becomes Your RAG Quality Ceiling
• [ 2026-06-23 ] When Verifiable Reasoning Fits in 3B Parameters
• [ 2026-06-23 ] When Business Teams Ship Agents, Who Owns Production
• [ 2026-06-23 ] Prompt Injection Is a Role-Perception Failure
• [ 2026-06-23 ] Rethinking Version Control When the Author Is an Agent
• [ 2026-06-22 ] When Multi-Agent Orchestration Hides Behind One API
• [ 2026-06-22 ] The Coding Agent That Writes 637 TB a Year
• [ 2026-06-22 ] Open Weights Were the Easy Part; Open Data Is the Point
• [ 2026-06-22 ] Fine-Tuning a Tiny Model Into a Reliable RAG Router
• [ 2026-06-21 ] Reliable Agentic RAG Is a Harness Problem, Not a Model Problem
• [ 2026-06-21 ] What One GPU Actually Costs You Per User
• [ 2026-06-21 ] Agents Need Throwaway Infra, Not Another OAuth Wall
• [ 2026-06-20 ] Why Agents Won't Just Fix Your Fused Kernels
• [ 2026-06-20 ] Why One Big Inference Pool Beats Many Small Ones
• [ 2026-06-19 ] When Codegen Is Cheap, Proof Becomes the Bottleneck
• [ 2026-06-19 ] Blast Radius Is the Resiliency Number That Counts
• [ 2026-06-19 ] MCP Auth Grows Up: One Login for Every Agent Tool
• [ 2026-06-19 ] Compressing Agent Output Optimizes the Wrong Number
• [ 2026-06-18 ] Local Models Aren't a Cheaper Opus, They're a Different Tool
• [ 2026-06-18 ] Agent Memory Is a Retrieval Problem, Not a Context Window
• [ 2026-06-18 ] The Model That Wins the Arena Isn't the One You Deploy
• [ 2026-06-18 ] Browser Agents Pay Their Real Tax Before the Model Runs
• [ 2026-06-17 ] When 'Anyone Can Ship' Meets Production Reality
• [ 2026-06-17 ] GLM-5.2 Pulls Open Weights Level with Proprietary Agents
• [ 2026-06-17 ] When the Training Set Comes with a Content Board
• [ 2026-06-17 ] The Local Model Inflection Point Is the Agentic Loop
• [ 2026-06-16 ] When 'Fix This Code' Gets Treated as a Munition
• [ 2026-06-16 ] Cohere Bets on Small and Sovereign for Agentic Coding
• [ 2026-06-16 ] Local Models for Coding: Throughput Isn't the Bottleneck
• [ 2026-06-16 ] A Homelab Agent That Can Open PRs but Not Deploy
• [ 2026-06-15 ] Salesforce Buys a Purpose-Built Support Model, Not a Wrapper
• [ 2026-06-15 ] OpenRouter's Fusion Bets on Ensembles Over Bigger Models
• [ 2026-06-15 ] AI Coding Agents Will Run Whatever You Print to Stdout
• [ 2026-06-15 ] When a 'Sovereign' LLM Is Mostly Someone Else's Weights
• [ 2026-06-14 ] Your Local LLM Bottleneck Is the BIOS, Not the Model
• [ 2026-06-14 ] Self-Hosting Your Coding Agent Is a Utilization Bet
• [ 2026-06-13 ] Open Weights Are an Ops Problem, Not a Manifesto
• [ 2026-06-13 ] Agentic Analytics Is a Trust Problem, Not a Model Problem
• [ 2026-06-13 ] Your Coding Agent Shouldn't Die With the Wi-Fi
• [ 2026-06-13 ] When the Planner Never Writes a Line of Code
• [ 2026-06-12 ] When a Proactive Agent Reaches Past Its Sandbox
• [ 2026-06-12 ] When an Agent's Autonomy Becomes a $6,500 AWS Bill
• [ 2026-06-10 ] When Your Model's Answer Is Legally Your Statement
• [ 2026-06-10 ] When Frontier Capability Breaks Your Data Boundary
• [ 2026-06-10 ] When Grep Beats Your Vector Store in the Agent Loop
• [ 2026-06-10 ] Fable 5's Real Story Is the Router, Not the Benchmarks
• [ 2026-06-09 ] The 1000-TPS Model and the Latency-Budget Math
• [ 2026-06-09 ] Apple Outsourced the Model and Kept the Architecture
• [ 2026-06-09 ] When Inference Gets Fast Enough to Change the Agent Loop
• [ 2026-06-09 ] When Code Benchmarks Graduate from Correct to Mergeable
• [ 2026-06-08 ] When Embedding Opacity Becomes a Retrieval Bug
• [ 2026-06-08 ] LLMs Aren't Eroding Engineering, They Erode the Ladder
• [ 2026-06-07 ] Agentic Coding Has a Token Accounting Problem
• [ 2026-06-07 ] The KV Cache Is a Compression Problem We Ignored
• [ 2026-06-07 ] When the Harness Becomes the Real Engineering Work
• [ 2026-06-07 ] The Sandbox Is the Hard Part of Agent Tool Use
• [ 2026-06-06 ] When Your Agent's Retry Logic Belongs in Postgres
• [ 2026-06-06 ] When Blaming the AI Needs a Permutation Test
• [ 2026-06-06 ] At Billion Scale, Vector Search Is an Engineering Problem
• [ 2026-06-06 ] Durable Execution Is Moving Into the Database
• [ 2026-06-05 ] Half the KV Cache for 3% Perplexity: A Trade Worth Watching
• [ 2026-06-05 ] An Agent That Finds Bugs Is Easy; Trusting It Is the Harness
• [ 2026-06-05 ] The Hard Part of Agentic Security Is Triage, Not Discovery
• [ 2026-06-05 ] Calibration-Free KV-Cache Quant Is the Real Unlock
• [ 2026-06-04 ] When Agents Get Good at Broken Access Control
• [ 2026-06-04 ] Blast Radius Is the Only Agent Safety Metric That Scales
• [ 2026-06-04 ] Capping the Blast Radius of Autonomous Agents
• [ 2026-06-04 ] What $1,500 of LLM Pentesting Says About Agentic Evals
• [ 2026-06-03 ] Why an AI Worm Is Really an Agentic Security Problem
• [ 2026-06-03 ] The Hard Part of Image RAG Isn't the Embedding Model
• [ 2026-06-03 ] The GPU Shortage Is Really a Software Shortage
• [ 2026-06-03 ] The Cheapest Place to Read an Image Is at Index Time
• [ 2026-06-02 ] When the Chain of Thought Comes Back Encrypted
• [ 2026-06-02 ] Scoping a Coding Agent Down to a Teaching Assistant
• [ 2026-06-02 ] When the Support Bot Becomes the Attack Surface
• [ 2026-06-02 ] OpenAI on AWS: Model Access Is Now Table Stakes
• [ 2026-05-30 ] Routing Is Becoming the Real AI Infrastructure
• [ 2026-05-29 ] Durable Agent Workflows Without the Workflow Engine
• [ 2026-05-28 ] Opus 4.8 and the Quiet Win of Fewer Tool Calls
• [ 2026-05-27 ] Claude Code Is Only as Good as Its Guardrails
• [ 2026-05-25 ] The Best Use of AI Coding Tools Is Slowing Down
• [ 2026-05-24 ] Your Inference Bill Is Really a Memory Bill
• [ 2025-11-05 ] Unlocking AI Success: Key Insights for Founders and Innovators
• [ 2025-11-05 ] Mastering the Art of Smart Investing: Insights for Long-Term Success
• [ 2025-11-05 ] Investment Strategies for Real-World Results: Lessons for Financial Success
• [ 2025-11-05 ] Mastering Global Investments: Key Insights for Long-Term Growth
• [ 2025-01-22 ] Deepseek R1 - stock market impact
• [ 2025-01-22 ] Deep Dive into Large Language Models (LLMs) like ChatGPT
• [ 2025-01-22 ] OpenAI Deep Research
• [ 2025-01-21 ] Deepseek R1 Paper review