Locate2u

The Locate2u AI Standard

How we measure AI capability across the team. The goal is not just to use AI, but to take ownership, build better products for our customers, and help redesign how we work.

Updated April 2026
Level 1
Using
"I use AI for basic tasks but my workflow has not changed."
  • Uses AI for writing, emails, and documentation
  • Generates simple graphics or mockups
  • Workflow is the same as pre-AI
  • Still picks up a couple of tickets and calls it a day
  • Waits to be told what to work on
  • Does not explore new tools or approaches
Level 2
Building
"I use AI to develop faster and prototype new ideas."
  • Uses AI for code generation, debugging, and testing
  • Builds prototypes and proof of concepts
  • Explores new features and product ideas independently
  • Output quality and speed are noticeably improved
  • Starting to remove their own roadblocks
  • Can present a concept within hours, not weeks
Level 3
Shipping
"I run multiple projects, get things live, and deliver real value to our customers."
  • Runs multiple projects at the same time
  • Completes full development cycles end to end
  • Gets new products and features into production
  • Thinks about what customers need and builds for it
  • Takes full ownership without needing to be managed
  • Identifies ways to make our customers more successful and acts on them
Level 4
Leading
"I redesign how we work and lift the entire team."
  • Does everything in Shipping, plus transforms how the team operates
  • Redesigns workflows and removes systemic roadblocks
  • Introduces new AI tools and processes for the whole team
  • Creates leverage: their work multiplies the output of others
  • Drives strategy, not just execution
  • Actively raises the bar for what the team considers normal

What this looks like by team

E
Engineering
Using
  • Uses Claude for autocomplete and quick answers
  • Asks AI to explain error messages
  • Completes assigned tickets at pre-AI pace
Building
  • Generates full components and modules with AI
  • Prototypes new app concepts in hours
  • Uses AI for test generation and code review
Shipping
  • Delivers complete features end to end and ships daily
  • Runs multiple workstreams in parallel
  • Ships products that solve real customer problems into production
Leading
  • Architects AI into the platform itself
  • Ships multiple times per day as the standard, not the exception
  • Rewrites team workflows so the entire engineering org moves faster
P
Product and Design
Using
  • Uses AI to tidy up copy and documentation
  • Generates simple wireframes or mockups
  • Process is the same as before AI
Building
  • Rapidly produces high fidelity prototypes
  • Uses AI to analyse competitor products and user behaviour
  • Generates specs, user stories, and feature briefs at speed
Shipping
  • Ships features so simple they require zero training
  • Handles complexity under the hood so the user experience stays effortless
  • Identifies what customers struggle with and builds solutions backed by data
Leading
  • Predicts user problems before they happen and resolves them proactively
  • Builds AI into the product so it gets smarter the more customers use it
  • Ensures customers never have a bad experience because the product anticipated it
S
Support and Operations
Using
  • Uses AI to draft replies and summarise tickets
  • Looks up information faster
  • Still manually handles every interaction with no measurement
Building
  • Builds workflows that solve common problems faster
  • Starts tracking and measuring customer issues with data
  • Creates knowledge bases that reduce repeat questions
Shipping
  • Measurably reduces resolution time with stats to prove it
  • Identifies recurring problems, gets to the root cause, and eliminates them
  • Deploys AI agents that resolve tickets before they escalate
Leading
  • Predicts customer problems and fixes them before the customer even knows
  • Turns support data into product improvements that prevent issues at source
  • Builds a support model where problems stop happening, not just get resolved faster
M
Sales and Marketing
Using
  • Uses AI to write emails and social posts
  • Generates basic ad copy and graphics
  • No change to pipeline or process
Building
  • Builds targeted campaigns and landing pages
  • Uses AI for lead research and outreach personalisation
  • Creates proposals and sales decks rapidly
Shipping
  • Runs campaigns that measurably grow lead volume and pipeline
  • Tracks spend and ROI across every channel with clear attribution
  • Grows the customer base by connecting the right customers with the right solutions
Leading
  • Builds AI tools that increase lead volume and close rates at scale
  • Automates manual tasks so the team focuses on high value conversations
  • Creates a closed loop between investment, customer acquisition, and customer success
A
Accounts and Finance
Using
  • Uses AI to draft reports and tidy up spreadsheets
  • Manually pulls numbers when asked
  • Reporting is reactive and takes days
Building
  • Builds dashboards and automated reports with AI
  • Starts measuring operational and financial performance in real time
  • Provides numbers to the business faster and with less manual effort
Shipping
  • Delivers the numbers the business needs to make decisions, when they need them
  • Identifies operational improvements and cost efficiencies backed by data
  • Measures return on investment across the work we are doing
Leading
  • Drives our ability to deliver cost efficient solutions to customers through financial insight
  • Provides investors with clear, measurable returns and performance data
  • Turns financial data into a strategic advantage that shapes how the business operates
Q
Quality Assurance
Using
  • Uses AI to help write test cases
  • Manually tests features one by one
  • Testing is a bottleneck that slows releases
Building
  • Builds automated test suites with AI assistance
  • Starts catching problems earlier in the development cycle
  • Reduces manual testing time through automation
Shipping
  • Enables development to push to live quickly by minimising risk
  • Automated testing covers critical paths so releases are safe and fast
  • Stops problems before they reach customers, not after
Leading
  • Predicts where problems will occur and prevents them before code is written
  • QA is fully embedded in the development pipeline with zero manual bottlenecks
  • Minimises impact to customers by ensuring quality is built in, not bolted on
⚡

Everything we build is for our customers.

Taking ownership is the critical difference. Every team member at every level should be asking: how does what I am doing today help our customers succeed? The people who take that question seriously, remove their own roadblocks, and get things into the hands of customers are the most valuable people on the team.