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  "whatIsVerbatim": "Only 'quote' fields, figure captions and 'abstract' are the authors' own words. Research questions follow the paper's wording where it states them. Takeaway, summaries, answers, definitions and method are the site's plain-language paraphrase.",
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 "name": "Goals as First-Class Abstractions in Human-AI Collaboration",
 "author": [
  {
   "@type": "Person",
   "name": "Lev Tankelevitch"
  },
  {
   "@type": "Person",
   "@id": "https://seanrintel.com/#sean-rintel",
   "name": "Sean Rintel",
   "url": "https://seanrintel.com/",
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    "https://scholar.google.com/citations?user=xc25GRgAAAAJ",
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    "https://www.microsoft.com/en-us/research/people/serintel/",
    "https://www.linkedin.com/in/seanrintel"
   ]
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 ],
 "datePublished": "2026-04",
 "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html",
 "citation": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026.",
 "bibtex": "@inproceedings{tankelevitch2026goals,\nauthor = {Tankelevitch, Lev and Rintel, Sean},\ntitle = {Goals as First-Class Abstractions in Human-AI Collaboration},\nbooktitle = {AutomationXP26 Workshop, CHI 2026},\nyear = {2026},\nmonth = {April},\npublisher = {ACM},\nurl = {https://matthiasbaldauf.com/automationxp26/papers/AutomationXP26_paper_0982.pdf},\n}",
 "abstract": "As AI assumes more of the material production in knowledge work, human effort shifts toward planning, orchestration, and evaluation, all of which revolves around goals. Yet goals remain poorly represented in knowledge work tools and workflows: implicit, unexpressed, or confused with outputs. Beyond their importance for human work, clear goals are fundamental to human-AI communication and collaboration. We review research establishing the value of explicit goals, show through a review of commercial tools that existing ecosystems support goal tracking but not goal articulation, alignment, or contextual use, and use meetings as a proving ground demonstrating that upstream goal articulation produces disproportionate downstream value for both humans and AI agents. We argue that goals should be encoded as first-class abstractions that drive human-AI collaborative workflows and that generative AI's natural-language capabilities make this a uniquely opportune moment. We outline six design requirements for goal-oriented human-AI collaborative systems.",
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 ],
 "fullTextAvailable": true,
 "takeaway": "Goals should be first-class abstractions that people and AI agents share and work from, because as AI takes over production, human work shifts to planning, orchestrating and evaluating around goals. Generative AI makes this feasible by handling fuzzy, evolving goals, and meeting intentionality shows the payoff of articulating them upfront.",
 "researchOverview": {
  "name": "Better Meetings",
  "page": "https://seanrintel.com/better-meetings.html",
  "json": "https://seanrintel.com/overviews/better-meetings.json",
  "markdown": "https://seanrintel.com/overviews/better-meetings.md",
  "thesis": "A meeting's purpose should shape everything about it, yet many meetings run without one stated. Good help with meeting goals moves people from wherever they start, with depth that fits the meeting.",
  "claimsThisPaperFeeds": [
   {
    "claim": "AI that asks what a meeting is for gets people thinking it through themselves",
    "role": "supporting evidence",
    "url": "https://seanrintel.com/better-meetings.html#m2"
   },
   {
    "claim": "A meeting's purpose is easily lost between meetings unless something carries it forward",
    "role": "supporting evidence",
    "url": "https://seanrintel.com/better-meetings.html#m5"
   }
  ],
  "otherPapers": [
   {
    "study": "Interviews: how people hold meeting goals",
    "title": "Mental Models of Meeting Goals: Supporting Intentionality in Meeting Technologies",
    "page": "https://seanrintel.com/publications/mental-models-of-meeting-goals-supporting-intentionality-in-meeting-technologies.html",
    "researchBrief": "https://seanrintel.com/publications/mental-models-of-meeting-goals-supporting-intentionality-in-meeting-technologies.json"
   },
   {
    "study": "Probe study: AI-drafted meeting plans",
    "title": "The CoExplorer Technology Probe: A Generative AI-Powered Adaptive Interface to Support Intentionality in Planning and Running Video Meetings",
    "page": "https://seanrintel.com/publications/the-coexplorer-technology-probe-a-generative-ai-powered-adaptive-interface-to-support-intentionality-in-planning-and-running-video-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/the-coexplorer-technology-probe-a-generative-ai-powered-adaptive-interface-to-support-intentionality-in-planning-and-running-video-meetings.json"
   },
   {
    "study": "Coaching study: an AI coach before real meetings",
    "title": "What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection",
    "page": "https://seanrintel.com/publications/what-does-success-look-like-catalyzing-meeting-intentionality-with-ai-assisted-prospective-reflection.html",
    "researchBrief": "https://seanrintel.com/publications/what-does-success-look-like-catalyzing-meeting-intentionality-with-ai-assisted-prospective-reflection.json"
   },
   {
    "study": "Probe study: goal check-ins during meetings",
    "title": "Are We On Track? AI-Assisted Active and Passive Goal Reflection During Meetings",
    "page": "https://seanrintel.com/publications/are-we-on-track-ai-assisted-active-and-passive-goal-reflection-during-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/are-we-on-track-ai-assisted-active-and-passive-goal-reflection-during-meetings.json"
   },
   {
    "study": "Recordings and design: looking back and ahead in meetings",
    "title": "Designing Interfaces that Support Temporal Work Across Meetings with Generative AI",
    "page": "https://seanrintel.com/publications/designing-interfaces-that-support-temporal-work-across-meetings-with-generative-ai.html",
    "researchBrief": "https://seanrintel.com/publications/designing-interfaces-that-support-temporal-work-across-meetings-with-generative-ai.json"
   },
   {
    "study": "Field experiment: nudging attention to meeting goals",
    "title": "Nudging Attention to Workplace Meeting Goals: A Large-Scale, Preregistered Field Experiment",
    "page": "https://seanrintel.com/publications/nudging-attention-to-workplace-meeting-goals-a-large-scale-preregistered-field-experiment.html",
    "researchBrief": "https://seanrintel.com/publications/nudging-attention-to-workplace-meeting-goals-a-large-scale-preregistered-field-experiment.json"
   },
   {
    "study": "System design: AI-mediated shared workspaces",
    "title": "Stund: Activity-Enriched Collaborative Workspaces Mediated by Artificial Intelligence",
    "page": "https://seanrintel.com/publications/stund-activity-enriched-collaborative-workspaces-mediated-by-artificial-intelligence.html",
    "researchBrief": "https://seanrintel.com/publications/stund-activity-enriched-collaborative-workspaces-mediated-by-artificial-intelligence.json"
   },
   {
    "study": "Conversation analysis: designing for the meeting",
    "title": "(Re)Configuring Hybrid Meetings: Moving from User-Centered Design to Meeting-Centered Design",
    "page": "https://seanrintel.com/publications/reconfiguring-hybrid-meetings-moving-from-user-centered-design-to-meeting-centered-design.html",
    "researchBrief": "https://seanrintel.com/publications/reconfiguring-hybrid-meetings-moving-from-user-centered-design-to-meeting-centered-design.json"
   },
   {
    "study": "Interviews and narration: what attention in video is for",
    "title": "Classification of Functional Attention in Video Meetings",
    "page": "https://seanrintel.com/publications/classification-of-functional-attention-in-video-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/classification-of-functional-attention-in-video-meetings.json"
   },
   {
    "study": "Interviews: low engagement as a choice",
    "title": "Low Engagement As a Deliberate Practice of Remote Participants in Video Meetings",
    "page": "https://seanrintel.com/publications/low-engagement-as-a-deliberate-practice-of-remote-participants-in-video-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/low-engagement-as-a-deliberate-practice-of-remote-participants-in-video-meetings.json"
   },
   {
    "study": "Research synthesis: collaboration and meetings",
    "title": "Collaboration and Meetings – Chapter 1 of the 2021 New Future of Work report",
    "page": "https://seanrintel.com/publications/collaboration-and-meetings.html"
   },
   {
    "study": "Telemetry and diaries: multitasking in remote meetings",
    "title": "Large Scale Analysis of Multitasking Behavior During Remote Meetings",
    "page": "https://seanrintel.com/publications/large-scale-analysis-of-multitasking-behavior-during-remote-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/large-scale-analysis-of-multitasking-behavior-during-remote-meetings.json"
   },
   {
    "study": "Survey and dashboard study: feedback on inclusive meetings",
    "title": "MeetingCoach: An Intelligent Dashboard for Supporting Effective and Inclusive Meetings",
    "page": "https://seanrintel.com/publications/meetingcoach-an-intelligent-dashboard-for-supporting-effective-inclusive-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/meetingcoach-an-intelligent-dashboard-for-supporting-effective-inclusive-meetings.json"
   },
   {
    "study": "Survey and diaries: chat alongside video meetings",
    "title": "The Promise and Peril of Parallel Chat in Video Meetings for Work",
    "page": "https://seanrintel.com/publications/the-promise-and-peril-of-parallel-chat-in-video-meetings-for-work.html",
    "researchBrief": "https://seanrintel.com/publications/the-promise-and-peril-of-parallel-chat-in-video-meetings-for-work.json"
   },
   {
    "study": "Diary study: video meetings in the pandemic",
    "title": "Meeting (the) Pandemic: Videoconferencing  Fatigue and Evolving Tensions of Sociality  in Enterprise Video Meetings During  COVID-19",
    "page": "https://seanrintel.com/publications/meeting-the-pandemic-videoconferencing-fatigue-and-evolving-tensions-of-sociality-in-enterprise-video-meetings-during-covid-19.html",
    "researchBrief": "https://seanrintel.com/publications/meeting-the-pandemic-videoconferencing-fatigue-and-evolving-tensions-of-sociality-in-enterprise-video-meetings-during-covid-19.json"
   },
   {
    "study": "Survey and telemetry: chat and voice in meetings",
    "title": "Virtual voices: Exploring individual differences in chat and verbal participation in virtual meetings",
    "page": "https://seanrintel.com/publications/virtual-voices-exploring-individual-differences-in-chat-and-verbal-participation-in-virtual-meetings.html",
    "researchBrief": "https://seanrintel.com/publications/virtual-voices-exploring-individual-differences-in-chat-and-verbal-participation-in-virtual-meetings.json"
   }
  ]
 },
 "whyItMatters": {
  "stateOfTheArt": {
   "summary": "Goals organise knowledge work, yet they rarely appear in its tools and artefacts, and the goal tools that exist support tracking rather than articulation.",
   "quote": "Goals often exist entirely in people's minds, either unformed or unexpressed, often leading to a confusion of outputs for outcomes",
   "location": "§1, pp. 1–2"
  },
  "contribution": {
   "summary": "The authors bring together goal-setting research, a review of commercial goal tools and meetings as a worked example. The authors argue that generative AI's ability to work with natural language removes the demand for premature precision that sank earlier goal-structuring systems.",
   "quote": "Goals can now be accommodated computationally. The open question is how to treat goal representations as living resources, open to interpretation and revision, not fixed contracts.",
   "location": "§5, p. 4"
  },
  "whoCares": {
   "summary": "Designers of knowledge work tools, collaborative systems and AI agent orchestration, and the many workers whose roles shift towards planning, orchestration and evaluation as AI takes on more production."
  }
 },
 "researchQuestions": [
  "We argue that human-AI collaborative systems should support the articulation of goals (desired outcomes) and encode goals as explicit abstractions. These abstractions should drive goal-oriented experiences that shape people's and AI agents' thinking, communication and workflows towards better outcomes rather than more outputs."
 ],
 "concepts": [
  {
   "term": "Goals",
   "definition": "The authors' deliberately broad definition:",
   "quote": "We define goals broadly as desired outcomes at any altitude, from task-level to strategic, hierarchically related, and often dynamically evolving",
   "location": "§1, p. 1"
  },
  {
   "term": "Goal articulation",
   "definition": "The step that no goal tool the authors reviewed supports:",
   "quote": "the reflective process of working out what you are actually trying to achieve",
   "location": "§3, p. 3"
  },
  {
   "term": "Goals as first-class representations",
   "definition": "Goals stored as structured, persistent objects linked to people, agents, artefacts and workflows. Why that matters:",
   "quote": "Making goals representationally first-class is what allows them to travel across tools and contexts.",
   "location": "§5, pp. 4–5"
  },
  {
   "term": "Outcomes versus outputs",
   "definition": "Desired results versus the artefacts produced along the way. The confusion the authors warn against:",
   "quote": "Meetings, decks, and shipped features are treated as ends rather than means.",
   "location": "§1, p. 2"
  }
 ],
 "method": {
  "design": "Position paper for a CHI 2026 workshop. It reviews research on the value of explicit goals (goal-setting theory and OKR practice) and commercial goal tools (task managers, project platforms and dedicated goal-setting products). Meetings serve as a worked example.",
  "setting": "Knowledge work in which human-AI teams collaborate.",
  "sample": "Commercial goal tools including Asana, ClickUp and Atlassian Goals. Prior research on meeting goals.",
  "analysis": "Argument and synthesis, leading to six design requirements for goal-oriented human-AI collaborative systems."
 },
 "findings": [
  {
   "headline": "Explicit goals do four jobs.",
   "summary": "Research on goal-setting theory and on OKR (Objectives and Key Results) practice shows that explicit goals direct attention, let collaborators coordinate without tracking every action, drive persistence and give a benchmark for judging results. The authors argue AI amplifies each of these, starting with attention:",
   "quote": "As AI cheapens the production of knowledge work, the cost to human attention increases",
   "location": "§2, p. 2",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s2-p-2",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§2, p. 2)"
  },
  {
   "headline": "Goal tools track, but don't help you think.",
   "summary": "In the authors' review of commercial goal tools (task managers, project platforms and dedicated goal-setting products), a few offer goal objects, alignment hierarchies and status rollups. But none helps people work out what they are actually trying to achieve, and their AI help only rewords goals.",
   "quote": "Existing tools assume goals are set once and occasionally reviewed. They are not built for a world where goals are living abstractions that shape how people and agents coordinate.",
   "location": "§3, p. 3",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s3-p-3",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§3, p. 3)"
  },
  {
   "headline": "Goals are missing where work happens.",
   "summary": "Goals in these tools stay inside single products and out of sight while people work. None carries goals across applications, shows them during the work itself, or uses them to direct AI agents.",
   "quote": "Goals are invisible at the point of work: no system provides situated goal cues during workflows, and no tool supports goal-guided agent orchestration.",
   "location": "§3, p. 3",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s3-p-3-2",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§3, p. 3)"
  },
  {
   "headline": "A little goal-setting pays off later.",
   "summary": "In meetings (the authors' worked example), earlier research found that prompting people to state a meeting's purpose and what success looks like when creating it led to better agendas and more focused meetings. The authors argue the same encoded goals could guide AI agents, for example:",
   "quote": "a recap agent can assess what was achieved rather than merely what was said, a scheduling agent can reason about whether the right people are invited",
   "location": "§4, p. 3",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s4-p-3",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§4, p. 3)"
  },
  {
   "headline": "Earlier goal systems demanded too much precision.",
   "summary": "Group Support Systems, workflow platforms and similar coordination tools tried to systematise the goals behind collaborative work and mostly failed. The authors argue generative AI can succeed where they did not, because it can work with goals stated loosely in natural language.",
   "quote": "Most foundered on the same problem: real goals are fuzzy, fluid, and contextdependent, while the systems designed to capture them demanded premature precision",
   "location": "§5, p. 4",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s5-p-4",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§5, p. 4)"
  },
  {
   "headline": "Six requirements, including agents that report on goals.",
   "summary": "The authors propose six requirements for goal-oriented systems. They are help with articulating goals, goals stored as persistent shared objects, surfacing alignment and misalignment, goal history, simulating how decisions cascade, and goal cues inside everyday workflows. For AI agents this means:",
   "quote": "AI agents should receive delegated goals and report progress against them, not merely against tasks completed.",
   "location": "§5, pp. 4–5",
   "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s5-pp-4-5",
   "cite": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026. (§5, pp. 4–5)"
  }
 ],
 "questions": [
  {
   "question": "Why do goals matter more when working with AI?",
   "answer": "Because as AI takes on more of the production, people's work shifts to deciding what to do, who should do it and whether it is on track. These all revolve around goals. Producing more becomes cheap, so attention to the right work becomes the bottleneck.",
   "source": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026.",
   "basedOn": [
    {
     "location": "§2, p. 2",
     "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s2-p-2"
    }
   ]
  },
  {
   "question": "What is the difference between a goal and an output?",
   "answer": "A goal is a desired outcome. An output is something produced, such as a meeting, a deck or a shipped feature. Because goals often stay unexpressed, people confuse the two and treat outputs as ends rather than means. Tools should help people and AI agents tell them apart.",
   "source": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026.",
   "basedOn": [
    {
     "location": "§5, pp. 4–5",
     "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s5-pp-4-5"
    }
   ]
  },
  {
   "question": "Isn't writing down goals just more admin?",
   "answer": "The authors argue a small upstream effort pays off downstream. Research on meeting intentionality found that prompting people to state a meeting's purpose and success conditions when creating it led to better agendas and more focused meetings. Those goals could also let a recap agent judge what was achieved.",
   "source": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026.",
   "basedOn": [
    {
     "location": "§4, p. 3",
     "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s4-p-3"
    }
   ]
  },
  {
   "question": "Why did earlier goal software fail, and what is different now?",
   "answer": "Earlier systems demanded that people specify fuzzy, changing goals precisely up front, so users worked around or abandoned them. Large language models can work with goals stated loosely in natural language, ask clarifying questions and follow how goals change, so goals can stay open to revision.",
   "source": "Lev Tankelevitch and Sean Rintel. 2026. Goals as First-Class Abstractions in Human-AI Collaboration. AutomationXP26 Workshop, CHI 2026.",
   "basedOn": [
    {
     "location": "§5, p. 4",
     "url": "https://seanrintel.com/publications/goals-as-first-class-abstractions-in-human-ai-collaboration.html#at-s5-p-4"
    }
   ]
  }
 ],
 "cites": [
  {
   "url": "https://seanrintel.com/publications/are-we-on-track-ai-assisted-active-and-passive-goal-reflection-during-meetings.html",
   "title": "Are We On Track? AI-Assisted Active and Passive Goal Reflection During Meetings",
   "location": "p. 5"
  },
  {
   "url": "https://seanrintel.com/publications/designing-interfaces-that-support-temporal-work-across-meetings-with-generative-ai.html",
   "title": "Designing Interfaces that Support Temporal Work Across Meetings with Generative AI",
   "location": "p. 7"
  },
  {
   "url": "https://seanrintel.com/publications/dynamic-prompt-middleware-contextual-prompt-refinement-controls-for-comprehension-tasks.html",
   "title": "Dynamic Prompt Middleware: Contextual Prompt Refinement Controls for Comprehension Tasks",
   "location": "p. 5"
  },
  {
   "url": "https://seanrintel.com/publications/mental-models-of-meeting-goals-supporting-intentionality-in-meeting-technologies.html",
   "title": "Mental Models of Meeting Goals: Supporting Intentionality in Meeting Technologies",
   "location": "p. 6"
  },
  {
   "url": "https://seanrintel.com/publications/nudging-attention-to-workplace-meeting-goals-a-large-scale-preregistered-field-experiment.html",
   "title": "Nudging Attention to Workplace Meeting Goals: A Large-Scale, Preregistered Field Experiment",
   "location": "p. 7"
  },
  {
   "url": "https://seanrintel.com/publications/the-metacognitive-demands-and-opportunities-of-generative-ai.html",
   "title": "The Metacognitive Demands and Opportunities of Generative AI",
   "location": "p. 7"
  },
  {
   "url": "https://seanrintel.com/publications/what-does-success-look-like-catalyzing-meeting-intentionality-with-ai-assisted-prospective-reflection.html",
   "title": "What Does Success Look Like? Catalyzing Meeting Intentionality with AI-Assisted Prospective Reflection",
   "location": "p. 6"
  }
 ],
 "quantitative": [],
 "implications": [
  {
   "summary": "Design goal articulation interfaces that support reflective, iterative thinking beyond form-filling and are intelligible to both humans and AI.",
   "quote": "First, designing goal articulation interfaces that support reflective, iterative thinking beyond form-filling, and ensure mutual intelligibility for humans and AI.",
   "location": "§6, p. 5"
  },
  {
   "summary": "Build interoperability layers so goal representations can travel across tools and contexts."
  },
  {
   "summary": "Develop goal-oriented experiences and evaluation frameworks that steer collaboration towards outcomes over outputs."
  }
 ],
 "limitations": [],
 "figures": [],
 "pageNumbersReferTo": "https://matthiasbaldauf.com/automationxp26/papers/AutomationXP26_paper_0982.pdf",
 "verified": "2026-10-25",
 "studyFigure": {
  "about": "The opening figure on this paper's page, made for the site with AI assistance from this verified brief. It is not the paper's own figure. Evidence entries index this file's quantitative, findings and limitations arrays.",
  "study": {
   "kind": "single",
   "heading": "The paper",
   "summary": "A position paper for a 2026 conference workshop on how people and AI agents work together. It reviews research on explicit goals and commercial goal tools, with meetings as a worked example.",
   "steps": [
    {
     "label": "Goal research",
     "detail": "Draws on goal-setting theory and Objectives and Key Results, a practice of setting objectives with measurable results."
    },
    {
     "label": "Goal tools",
     "detail": "Examines commercial task managers, project platforms and goal-setting products, such as Asana, ClickUp and Atlassian Goals."
    },
    {
     "label": "Meetings example",
     "detail": "Uses earlier research on meeting goals to show what stating goals upfront can achieve."
    },
    {
     "label": "Requirements",
     "detail": "Argues towards six design requirements for systems in which people and AI agents work from shared goals."
    }
   ]
  },
  "findings": {
   "heading": "What the paper argues",
   "legend": null,
   "stages": [
    {
     "title": "Why goals matter more with AI",
     "sub": "the argument from goal research",
     "items": [
      {
       "dir": "none",
       "text": "The paper argues explicit goals focus attention, aid coordination, sustain effort and benchmark results.",
       "detail": "The paper draws on goal-setting theory and Objectives and Key Results practice. It argues AI amplifies each role, because cheaper production raises the cost to human attention.",
       "evidence": [
        "findings[0]"
       ]
      },
      {
       "dir": "none",
       "text": "The paper argues earlier goal systems failed because they demanded too much precision.",
       "detail": "Group support and workflow systems needed exact goals, while real goals are fuzzy and change. The paper argues generative AI can work with goals stated loosely.",
       "evidence": [
        "findings[4]"
       ]
      }
     ]
    },
    {
     "title": "What current goal tools miss",
     "sub": "the paper's review of commercial goal tools",
     "items": [
      {
       "dir": "none",
       "text": "In the paper's review, no goal tool helped people work out what they wanted to achieve.",
       "detail": "A few tools offer goal objects, alignment hierarchies and status rollups. The tools' AI help only rewords goals.",
       "evidence": [
        "findings[1]"
       ]
      },
      {
       "dir": "none",
       "text": "In the paper's review, no goal tool used goals across apps or to direct AI agents.",
       "detail": "Goals stayed inside single products and out of sight while people worked.",
       "evidence": [
        "findings[2]"
       ]
      }
     ]
    },
    {
     "title": "What to build",
     "sub": "a worked example and design requirements",
     "items": [
      {
       "dir": "none",
       "text": "Meeting research cited by the paper found stating a purpose upfront led to better agendas.",
       "detail": "Prompting people to state purpose and success when creating a meeting also led to more focused meetings. The paper argues AI agents could work from such goals.",
       "evidence": [
        "findings[3]"
       ]
      },
      {
       "dir": "none",
       "text": "The paper proposes six requirements for systems where people and AI agents share goals.",
       "detail": "Help to articulate goals, persistent shared goals, signs of alignment, goal history, simulated decisions and goal cues in daily work. AI agents would report progress against goals.",
       "evidence": [
        "findings[5]"
       ]
      }
     ]
    }
   ]
  },
  "keyTerm": "first-class abstractions",
  "takeaway": "Treating goals as first-class abstractions, shared and explicit, can help people and AI agents aim at outcomes rather than outputs. Generative AI may make this practical by working with fuzzy, changing goals."
 }
}