BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//talks.osgeo.org//qgis-uc2026//speaker//LJQ3PP
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-qgis-uc2026-LLQG7R@talks.osgeo.org
DTSTART;TZID=CET:20261005T123000
DTEND;TZID=CET:20261005T130000
DESCRIPTION:AI coding assistants are easy to overhype. In practice\, the in
 teresting question is much narrower: where do agentic coding tools actuall
 y help when building and maintaining a real QGIS plugin?\n\nThis talk pres
 ents lessons from developing qfit\, a QGIS plugin for importing\, analysin
 g\, and publishing personal fitness activity data\, using OpenClaw as an a
 gentic coding environment. Rather than treating AI as a magic code generat
 or\, I will focus on practical workflows: breaking work into small reviewa
 ble changes\, using agents to explore code\, draft implementations\, refac
 tor modules\, and strengthen tests\, while keeping a human firmly responsi
 ble for architecture\, validation\, and release quality.\n\nI will share w
 hat worked well\, where the approach failed or created extra review burden
 \, and which guardrails mattered most\, especially around testing\, CI\, c
 ode review\, and incremental design in a PyQGIS codebase. Attendees will l
 eave with concrete patterns for using agentic coding in QGIS plugin develo
 pment without lowering engineering standards.\n\nThis session is aimed at 
 developers and technical QGIS users who are curious about AI-assisted plug
 in development but want concrete practices rather than hype.
DTSTAMP:20260724T230556Z
LOCATION:Bridge 2
SUMMARY:Building a QGIS plugin with agentic coding: lessons from qfit and O
 penClaw - Emmanuel Belo
URL:https://talks.osgeo.org/qgis-uc2026/talk/LLQG7R/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-qgis-uc2026-SRUFPN@talks.osgeo.org
DTSTART;TZID=CET:20261006T153000
DTEND;TZID=CET:20261006T160000
DESCRIPTION:Fitness activity data usually lives inside proprietary platform
 s\, which makes it hard to analyse\, combine with other spatial data\, or 
 publish in reusable map products. qfit is a QGIS plugin that brings that d
 ata back into an open GIS workflow.\n\nIn this talk\, I will present qfit\
 , a plugin that imports fitness activities from Strava into a local GeoPac
 kage\, turns them into analysis-ready QGIS layers\, and supports a complet
 e workflow from import to publication. The plugin covers three main use ca
 ses: importing and synchronising activities\, visualising and filtering th
 em in QGIS\, and generating PDF atlas outputs with activity pages\, summar
 ies\, and profile-ready metadata.\n\nI will show how personal activity dat
 a can become a real geospatial dataset: styled\, filtered\, queried\, comb
 ined with basemaps\, and prepared for high quality print layouts. I will a
 lso share a few practical lessons from building the plugin\, including han
 dling detailed track geometry\, temporal data\, and atlas-oriented layer d
 esign.\n\nThis session is aimed at QGIS users and plugin developers intere
 sted in personal mobility\, sports data\, and new geospatial workflows bui
 lt on open tools.
DTSTAMP:20260724T230556Z
LOCATION:Bridge 2
SUMMARY:qfit: Bringing personal fitness data into QGIS for analysis\, filte
 ring\, and atlas production - Emmanuel Belo
URL:https://talks.osgeo.org/qgis-uc2026/talk/SRUFPN/
END:VEVENT
END:VCALENDAR