PRECISION FEDERAL · MARKET & TRENDS
Software and platforms
Building, replacing and running the software a business actually depends on.
Software and platforms
Recent posts
Software and platforms
Replacing the Spreadsheet That Runs a Department
Software and platforms
Automating a Process Nobody Has Documented
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Search That People Trust
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SOC 2 for an AI Company, Minimally
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Scheduling Templates and Real Capacity
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Integrating Two Systems That Were Never Meant to Talk
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Shared Responsibility With Your Cloud Provider Under CMMC
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Mobile or Web for an Internal Tool
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Notifications People Do Not Turn Off
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Software for a Business That Runs on Email
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A Mobile App for a Business That Has None
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Voice and Phone Automation That Does Not Infuriate People
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Quoting and Estimating Tools
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Automating Back-Office Work at a Mid-Size Company
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Multi-Tenant Architecture From Day One
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Classifying Support Tickets
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Migrating Off a Legacy System Without a Freeze
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File Processing at Volume
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Authentication and Permissions, Done Once
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An API for Your Partners
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Who Owns the Code You Paid For
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Search Over Your Own Documents
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Confidential Computing: What It Does and Does Not Do
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Supporting a Customer Whose Data You Cannot See — Precision Federal
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A Single Source of Truth People Actually Use
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Replacing a Legacy Internal App
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Workflow Engines and When You Need One
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Latency Budgets for Conversational AI
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Telemetry That Is Safe by Construction
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A Design System for an Internal Tool
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Support and Maintenance, Honestly
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Migrating Off Spreadsheets Without Breaking the Business
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Zero Data Retention Architecture for AI Products
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Multi-Tenancy Isolation for AI Inference
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Building with Claude in Production
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Building an Internal Platform Your Team Will Use
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Automating email triage
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How to Write a Brief for Software You Cannot Specify Yet
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Why Software Projects Slip, and What to Do About It
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A Customer Portal Worth Logging Into
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Shipping Your AI Product Into a Customer's VPC
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Testing What Cannot Be Exhaustively Tested
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Capacity Planning for Bursty Inference
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Kubernetes for GPU Workloads: What Changes
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Spot and Preemptible Instances for ML Workloads
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ML Observability Beyond Dashboards
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Evaluation Infrastructure for Production Models
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Python Packaging and Deployment That Holds
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Observability for a Small Engineering Team
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An Admin Panel Worth Using
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Building a Search That Actually Works
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Webhooks That Do Not Lose Events
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Background Jobs and Idempotency
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Caching Strategies That Do Not Lie to You
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Choosing a Vector Database, Honestly
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Postgres at Scale Before You Shard
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