Agentic software development with bounded authority
Engineer agents through explicit goals, typed tools, controlled state, least privilege, budgets, evaluation and recoverable execution.
Tony Kim Founder and CEO Read guide Founder and CEO
Tony Kim
Tony writes about applied AI, dependable product engineering and the systems that turn complex response work into controlled delivery.
View on LinkedInTony Kim is the founder and CEO of Zephior. He works across product, engineering and commercial delivery, with a focus on turning language-heavy work into software that can be evaluated, operated and improved.
Before founding Zephior, Tony worked with enterprise financial-technology customers at Ripple. His perspective combines software architecture, AI evaluation and direct experience with complex RFP and buyer-response processes.
62 guides
Published field guides
Insights
Tony Kim Founder and CEO Read guide AI software engineering beyond the model demonstration
Engineer AI software with behavioral contracts, deterministic control planes, evaluation evidence, safe delivery, observability and accountable operations.
Tony Kim Founder and CEO Read guide AI workflow automation that survives real operations
A practical method for selecting, designing and operating AI workflow automation with explicit state, evidence, exceptions, review and ROI.
Tony Kim Founder and CEO Read guide How to build an AI evaluation dataset for a real product
Create a product-specific evaluation asset with representative cases, explicit judgments, critical slices, leakage control and production feedback.
Tony Kim Founder and CEO Read guide How to design meaningful human review for AI products
Turn human oversight into a measurable product subsystem with clear authority, evidence, routing, queue controls and escalation.
Tony Kim Founder and CEO Read guide How to evaluate an AI product idea before building it
Test whether AI improves a real decision, can be evaluated with available data and remains valuable after failure handling, review and operating cost.
Tony Kim Founder and CEO Read guide How to monitor production AI behavior, not just uptime
Build a privacy-aware control loop for AI inputs, outputs, quality slices, human intervention, drift, incidents, cost and safe rollback.
Tony Kim Founder and CEO Read guide How to select an AI model for a real application
Choose a model against the application’s cases, controls and operating constraints, then preserve the evidence and exit options needed when models change.
Tony Kim Founder and CEO Read guide Human-in-the-loop automation that provides real control
Design human review around consequence, uncertainty, authority, evidence, queue capacity, intervention rights and measurable learning.
Tony Kim Founder and CEO Read guide Open-source AI models for enterprise products
Evaluate open and open-weight AI models through rights, task quality, provenance, hosting, security, operating cost and long-term ownership.
Tony Kim Founder and CEO Read guide How to prevent AI hallucinations in proposals
A practical control model for source-grounded proposal answers, visible evidence gaps, claim-level review and defensible AI-assisted submissions.
Tony Kim Founder and CEO Read guide Production AI product readiness checklist
A rigorous AI production checklist for product value, evaluation, data, security, reliability, operations, economics and controlled release.
Tony Kim Founder and CEO Read guide Solutions
AI evaluation platform implementation for product teams
Build the test corpus, runners, graders, trace model, release gates and governance needed to evaluate AI products repeatedly as they change.
Tony Kim Founder and CEO Read guide AI model migration service for production systems
Migrate models and providers through coupling discovery, behavioral baselines, adapter design, comparative evaluation, staged traffic and rollback.
Tony Kim Founder and CEO Read guide AI MVP development that produces a real decision
A practical guide to AI MVP development with a falsifiable user outcome, representative evaluation, controlled risk and a credible path to production.
Tony Kim Founder and CEO Read guide AI software development in Switzerland
A production-focused guide to scoping, building and operating custom AI software in Switzerland with explicit data, model, security and review choices.
Tony Kim Founder and CEO Read guide AI system evaluation service for release decisions
Independent AI evaluation for task quality, grounding, safety, robustness, human oversight, latency, cost and production release evidence.
Tony Kim Founder and CEO Read guide Custom AI application development for real workflows
Plan a custom AI application around a valuable user job, proprietary context, measurable behavior, safe integration and accountable operations.
Tony Kim Founder and CEO Read guide Data enrichment automation with field-level provenance
Automate entity resolution, source retrieval, field extraction, conflict handling, freshness and controlled write-back for trusted business data.
Tony Kim Founder and CEO Read guide Document AI development for real business files
Build document AI that preserves layout, tables, provenance, review and downstream output across PDF, Word, Excel, scans and images.
Tony Kim Founder and CEO Read guide Enterprise AI agent development for production work
A production guide to building enterprise AI agents with bounded tools, explicit permissions, durable state, evaluation and accountable release.
Tony Kim Founder and CEO Read guide Human review system development for AI workflows
Engineer review queues, case evidence, decision controls, escalation, quality assurance and feedback so human oversight works under real load.
Tony Kim Founder and CEO Read guide Legacy software modernization with AI and verified change
Use AI for system archaeology, test creation and migration support while controlling behavior, data, interfaces, security and incremental cutover.
Tony Kim Founder and CEO Read guide LLM application development with measurable behavior
Build an LLM application around a defined job, evaluation corpus, controlled context, secure tool boundaries, observability and safe failure paths.
Tony Kim Founder and CEO Read guide Proposal software for Swiss and European response teams
Evaluate proposal software for multilingual Swiss teams using evidence quality, workflow control, data handling, adoption and measurable operating fit.
Tony Kim Founder and CEO Read guide RAG application development for dependable answers
A product engineering guide to RAG systems with source ingestion, retrieval, citations, permissions, evaluation and production monitoring.
Tony Kim Founder and CEO Read guide Industries
AI product engineering for healthcare software
Engineer healthcare AI around intended use, clinical workflow, representative evidence, patient safety, interoperability and controlled product change.
Tony Kim Founder and CEO Read guide AI product engineering for insurance operations
Engineer insurance AI around policy truth, claim evidence, decision authority, representative evaluation and resilient human operations.
Tony Kim Founder and CEO Read guide AI product engineering for legal technology
Build legal AI products around authoritative sources, matter boundaries, citation verification, professional review and task-specific evaluation.
Tony Kim Founder and CEO Read guide AI product engineering for logistics technology
Build logistics AI products around event truth, physical constraints, uncertain forecasts, interoperable identities and accountable operational decisions.
Tony Kim Founder and CEO Read guide AI software engineering for fintech with controlled state
Build fintech AI around deterministic ledgers, evidence, authorization, model governance, resilience, audit and reversible releases.
Tony Kim Founder and CEO Read guide Geospatial AI software development with spatial evidence
Engineer geospatial AI around coordinate systems, time, resolution, lineage, topology, regional evaluation and validated operational exports.
Tony Kim Founder and CEO Read guide Public-sector AI software development with accountable service
Build public AI services around mandate, accessibility, transparent case records, human recourse, measurable benefit and supplier-independent operations.
Tony Kim Founder and CEO Read guide Comparisons
AI agent vs AI copilot: choose an authority boundary
Compare AI agents and copilots by initiative, tools, approvals, product experience, security, evaluation, recovery and operational ownership.
Tony Kim Founder and CEO Read guide AI agents vs RPA for business process automation
Compare AI agents and RPA by workflow variability, decision authority, integration, controls, economics and the best hybrid operating model.
Tony Kim Founder and CEO Read guide AI feature vs AI product: choose scope from the user job
Decide whether AI belongs in an existing workflow or needs a standalone product by user job, data, risk, distribution, economics and ownership.
Tony Kim Founder and CEO Read guide AI product studio vs agency: choosing a delivery model
Compare AI product studios and development agencies by discovery, evaluation, engineering, risk, deployment, commercial model and knowledge transfer.
Tony Kim Founder and CEO Read guide AI prototype vs production AI product: cross the evidence gap
Compare AI prototypes and production products by learning goal, evaluation, architecture, security, user experience, operations, cost and ownership.
Tony Kim Founder and CEO Read guide Deterministic vs agentic automation: design the control plane
Compare deterministic and agentic automation by process variation, authority, testing, exceptions, security, operations, cost and hybrid design.
Tony Kim Founder and CEO Read guide Intelligent document processing vs OCR: text is not the outcome
Compare IDP and OCR by transcription, document classes, field extraction, validation, human review, integration, evidence and business outcomes.
Tony Kim Founder and CEO Read guide No-code vs custom AI automation: choose the delivery boundary
Compare visual workflow platforms and custom AI automation by speed, fit, connectors, testing, security, observability, scale, cost and exit.
Tony Kim Founder and CEO Read guide Open-source vs proprietary AI models
Compare open-weight and proprietary AI models using measured task quality, data flow, licensing, operations, change risk and total cost.
Tony Kim Founder and CEO Read guide RAG vs fine-tuning: choose knowledge, behavior or both
Compare retrieval-augmented generation and fine-tuning by factual knowledge, behavior, citations, data, evaluation, security, latency and operations.
Tony Kim Founder and CEO Read guide RFP software vs generative AI chat: what each controls
Compare RFP software and general AI chat by source evidence, requirements, permissions, collaboration, review, document handling and accountability.
Tony Kim Founder and CEO Read guide Ziva vs AutogenAI: proposal workflow and source control
Compare Ziva and AutogenAI across proposal lifecycle coverage, knowledge and sources, writing, review, Word workflows, deployment, speed claims and buyer fit.
Tony Kim Founder and CEO Read guide Ziva vs Loopio: a factual proposal software comparison
Compare Ziva and Loopio on workflow, governed knowledge, citations, file handling, collaboration, deployment and buyer fit.
Tony Kim Founder and CEO Read guide Ziva vs Responsive: compare response operations and evidence
Compare Ziva and Responsive on RFP workflow, trusted knowledge, source verification, human approval, deployment and buyer fit.
Tony Kim Founder and CEO Read guide Glossary
AI agent: meaning, architecture and production controls
An AI agent pursues a goal through model-guided decisions and tools, requiring explicit limits on identity, actions, state and human approval.
Tony Kim Founder and CEO Read guide AI guardrails: controls, limits and production testing
AI guardrails constrain inputs, outputs and actions, but no single filter guarantees safety. Design layered controls around the actual product consequence.
Tony Kim Founder and CEO Read guide AI model evaluation: test sets, metrics and gates
AI evaluation measures whether a model-enabled system meets task, risk, latency and cost requirements on representative cases before and after launch.
Tony Kim Founder and CEO Read guide Embeddings in AI: meaning, retrieval and evaluation
Embeddings turn content into numerical representations for comparison and retrieval. Learn what determines useful similarity in a production system.
Tony Kim Founder and CEO Read guide Fine-tuning AI models: meaning, choices and controls
Fine-tuning changes a pretrained model for a defined task or behavior. Learn when it helps, what evidence it needs and how to operate it safely.
Tony Kim Founder and CEO Read guide Human in the loop: meaningful oversight for AI
Human-in-the-loop AI places a person at a defined decision point, with enough evidence, authority and time to review or change the outcome.
Tony Kim Founder and CEO Read guide Intelligent document processing: IDP system guide
Intelligent document processing turns variable files into validated structured data through capture, classification, extraction and review.
Tony Kim Founder and CEO Read guide Large language model: LLM meaning and production use
A large language model predicts and generates language, but a reliable AI product also needs context, controls, evaluation and software operations.
Tony Kim Founder and CEO Read guide Model Context Protocol: tools, resources and boundaries
Understand MCP clients, servers, tools, resources and prompts, plus the security and reliability controls an enterprise integration still needs.
Tony Kim Founder and CEO Read guide Model drift: detection, diagnosis and response in AI
Model drift is a production change that can invalidate expected AI behavior. Learn how to monitor outcomes, find causes and respond with control.
Tony Kim Founder and CEO Read guide Prompt injection: risks, examples and defenses
Prompt injection occurs when untrusted instructions alter intended model behavior, especially when an LLM can access sensitive context or tools.
Tony Kim Founder and CEO Read guide Retrieval-augmented generation: RAG system guide
Retrieval-augmented generation gives a language model selected external context, helping applications answer from current, private or cited sources.
Tony Kim Founder and CEO Read guide AI tool calling: schemas, permissions and safe execution
Tool calling lets a model request structured operations. Learn how applications validate arguments, authorize effects and verify real outcomes.
Tony Kim Founder and CEO Read guide Vector database: embeddings, search and production choices
A vector database stores and searches embeddings by similarity. Learn what it does, when it helps and how to test relevance, filters, latency and change.
Tony Kim Founder and CEO Read guide Workflow orchestration: state, retries and recovery
Workflow orchestration coordinates multi-step work across systems, people and AI while preserving state, policy, observability and recovery.
Tony Kim Founder and CEO Read guide